nathansutton/data-science-job-descriptions huggingface dataset:
Staff Data Scientist Search Recommendation at Faire

About this role
Faire is using machine learning to change wholesale and help local retailers compete with Amazon and big box stores. Our experienced data scientists and machine learning engineers are developing solutions related to discovery, ranking, search, recommendations, logistics, underwriting, and more - all with the goal of helping local retail thrive.
The Data Science team owns a wide variety of algorithms and models that power the marketplace. We care about building machine learning models that help our customers thrive. 
As a member of Search for the Data Science team you’ll be responsible for developing machine learning-powered search ranking models and adding personalization to our search and discovery. You’ll determine answers to questions like, how relevant is this product to this retailer and how can we infer that in real-time? Can we create real-time embeddings of users' interests and use them to power rankings? How can we improve purchase flow? What techniques can we use to enable our A/B tests to more quickly converge when dealing with low sample sizes?
Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there!
You’re excited about this role because…

You’ll be able to work on cutting-edge search query and understanding problems combining a wide variety of data about our retailers, brands and products
You want to use machine learning to help local retailers and independent brands succeed
You want to be a foundational team member of a fast growing company
You like to solve challenging problems related to a two-sided marketplace

Qualifications

5+ years of industry experience using machine learning to solve real-world problems
Experience with search/query processing for product development
Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch,Solr, FAISS)
Strong programming skills
An excitement and willingness to learn new tools and techniques
Experience with relational databases and SQL
The ability to contribute to team strategy and to lead model development without supervision
Strong communication skills and the ability to work with others in a closely collaborative team environment 

Great to Haves:

Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
Ability to quickly implement state of the art algorithms from an academic paper
Previous experience on graph neural network and/or language models and deep learning

Salary Range
California / New York: the pay range for this role is $203,000 - $279,000 per year. 
Colorado / Washington / New Jersey: the pay range for this role is $183,000 - $251,000 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Senior Data Scientist Search Recommendation at Faire

About this role
Faire is using machine learning to change wholesale and help local retailers compete with Amazon and big box stores. Our experienced data scientists and machine learning engineers are developing solutions related to discovery, ranking, search, recommendations, logistics, underwriting, and more - all with the goal of helping local retail thrive.
The Data Science team owns a wide variety of algorithms and models that power the marketplace. We care about building machine learning models that help our customers thrive. 
As a member of Search for the Data Science team you’ll be responsible for developing machine learning-powered search ranking models and adding personalization to our search and discovery. You’ll determine answers to questions like, how relevant is this product to this retailer and how can we infer that in real-time? Can we create real-time embeddings of users' interests and use them to power rankings? How can we improve purchase flow? What techniques can we use to enable our A/B tests to more quickly converge when dealing with low sample sizes?
Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there!
You’re excited about this role because…

You’ll be able to work on cutting-edge search query and understanding problems combining a wide variety of data about our retailers, brands and products
You want to use machine learning to help local retailers and independent brands succeed
You want to be a foundational team member of a fast growing company
You like to solve challenging problems related to a two-sided marketplace

Qualifications

3+ years of industry experience using machine learning to solve real-world problems
Experience with search/query processing for product development
Experience with traditional, semantic, and hybrid search frameworks (e.g. Elasticsearch,Solr, FAISS)
Strong programming skills
An excitement and willingness to learn new tools and techniques
Experience with relational databases and SQL
The ability to contribute to team strategy and to lead model development without supervision
Strong communication skills and the ability to work with others in a closely collaborative team environment 

Great to Haves:

Highly recommended: Master’s or PhD in Computer Science, Statistics, or related STEM fields
Ability to quickly implement state of the art algorithms from an academic paper
Previous experience on graph neural network and/or language models

Salary Range
California / New York: the pay range for this role is $173,000 - $238,000 per year. 
Colorado / Washington / New Jersey: the pay range for this role is $156,000 - $214,500 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Senior Data Scientist Retailer at Faire

About this role
Faire leverages the power of machine learning and data insights to revolutionize the wholesale industry, enabling local retailers to compete against giants like Amazon and big box stores. Our highly skilled team of data scientists and machine learning engineers specialize in developing algorithmic solutions for notification and recommender systems, advertising attribution, and LTV predictions. Our ultimate goal is to empower local retail businesses with the tools they need to succeed.
At Faire, the Data Science team is responsible for creating and maintaining a diverse range of algorithms and models that power our marketplace. We are dedicated to building machine learning models that help our customers thrive.
As a Data Scientist on the Retailer team, you will work on solving shipping cost problems by leveraging machine learning models, engineering and analysis skills. You will help drive the adoption of the Ship-with-Faire (SWF) program among brands and optimize the SWF program economics.
Our team already includes experienced Data Scientists and Machine Learning Engineers from Uber, Airbnb, Square, Facebook, and Pinterest. Faire will soon be known as a top destination for data scientists and machine learning, and you will help take us there! 
What you’ll do 

Build ML models that provide accurate shipping cost estimates. Engineer new features to improve model performance. These models may use information from carriers (USPS/UPS/FedEx) and be both performant and explainable.
Maximize customer retention while keeping contribution profits in check.
Develop an in-house utility that can expose information about the shipping cost predictions, making model debugging more efficient for internal stakeholders.
Tackle complex issues inherent in managing a two-sided marketplace. Your ability to identify and address these challenges will be critical to our continued growth and success.

Qualifications

Strong machine learning skills and 3+ years of experience productionizing machine learning models (Sklearn, XGBoost, Predictive Modeling, or Deep Learning
Strong programming skills (Python, Java, Kotlin, C++)
Knowledge of statistical techniques such as experimentation and causal inference
SQL or other database querying experience preferred
An excitement and willingness to learn new tools and techniques

Salary Range
California / New York: the pay range for this role is $173,000 - $238,000 per year. 
Colorado / Washington / New Jersey: the pay range for this role is $156,000 - $214,500 per year.
This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.
Principal Machine Learning Scientist at Atlassian

Working at Atlassian
Atlassian can hire people in any country where we have a legal entity. Assuming you have eligible working rights and a sufficient time zone overlap with your team, you can choose to work remotely or from an office (unless it’s necessary for your role to be performed in the office). Interviews and onboarding are conducted virtually, a part of being a distributed-first company.
Atlassian is looking for a remote Principal Machine Learning Scientist to join our Core Machine Learning team. The Core Machine Learning team builds and deploys ML modeling solutions to increase revenue generation, expand our active user base and enhance internal productivity and efficiency. This is a unique opportunity to work in a collaborative environment and implement the latest machine learning techniques, including LLM (large language models).
Your future team
The Core Machine Learning team sits within the Data Science group in the Atlassian Corporate Engineering Organization. We work with several business teams in GTM, growth, product, and many other teams providing machine learning infrastructure and modeling applications. Our team consists of ML scientists and engineers, and provides many opportunities for collaboration, knowledge sharing, and individual growth. The team is split geographically between the US and Australia, supporting partners across the regions.
You will report to the Core Machine Learning Senior Manager.
What you'll do
As a Principal Machine Learning Scientist, you will lead the development of advanced machine learning algorithms, collaborating with business partners, engineering, and analytics teams to personalize the customer buyer journey across several touch points which include paid ads, SEO content, web pages and in-product experiences.You will lead Generative AI projects aimed at improving customer conversion funnels, streamlining content and creative creation processes, and developing self-serve tooling to empower Atlassian with valuable data insights.Explain data science concepts to non-technical, diverse audiences and create a compelling story.Be a tech lead for more junior Machine Learning Scientists, providing technical guidance.
Your background
Master and above degree in a quantitative subject (Statistics, Mathematics, Computer Science, Operations Research, or relevant work experience)5+ years of related industry experience in the machine learning domainExpertise in Python with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, Databricks)Experience building and scaling machine learning models in business applications using large amounts of dataExperience building NLP related applicationsFocus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future"Agile development mindset, appreciating the benefit of constant iteration and improvement
Machine Learning Researcher Phd at Figma

We’re looking for engineers with a background in machine learning & artificial intelligence to improve our products and build new capabilities. You'll be driving fundamental and applied research in this area. You’ll be combining industry best practices and a first-principles approach to design and build ML models and infrastructure that will improve Figma’s design and collaboration tool. 

 
What you’ll do at Figma:


Drive fundamental and applied research in ML/AI, with Figma product use cases in mind 

Formulate and implement new modeling approaches both to improve the effectiveness of Figma’s current models as well as enable the launch of entirely new AI-powered product features

Work in concert with other ML researchers, as well as product and infrastructure engineers to productionize new models and systems to power features in Figma’s design and collaboration tool


Explore the boundaries of what is possible with the current technology set and experiment with novel ideas


We'd love to hear from you if you have:


Recently obtained a PhD or equivalent experience in an industry research role in AI, Computer Science or a related field

Demonstrated expertise in machine learning with publication record in relevant conferences, or a track record in applying machine learning techniques to products

Experience in Python and machine learning frameworks (such as PyTorch, TensorFlow)

Experience building systems based on deep learning, natural language processing, computer vision, and/or generative models

Experience solving sophisticated problems and comparing alternative solutions, trade-offs, and diverse points of view to determine a path forward

Experience communicating and working across functions to drive solutions. 

At Figma, one of our values is Grow as you go. We believe in hiring smart, curious people who are excited to learn and develop their skills. If you’re excited about this role but your past experience doesn’t align perfectly with the points outlined in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles. 
Read more about our team 

Investing in Figma: The Decade of Design
How work is changing at Figma
Figma's next product is a multiplayer whiteboard called FigJam
Software Design Startup Figma Is Now Worth $10 Billion
Figma's Musical!
The Future of Design Systems is Automated

#LI-CC1
Lead Data Scientist Pricing at Angi

About the Role




Our Applied Data Science team is tackling challenges such as homeowner-contractor matching, forecasting key business metrics, and using predictive models to optimize consumer experience. This role will give you the opportunity to shape the vision and implementation of our 2-sided marketplace pricing strategy using state-of- the-art machine learning infrastructure and big data processing tools.




What you’ll do 





Leading and developing a best-in-class data science pricing program


Creating a strategic pricing vision and develop initiatives aimed to accomplish the vision


Building productive and efficient relationships with stakeholders across marketing, data/analytics,
product, and finance


Creating mathematical and data driven solutions for difficult pricing problems at scale


Developing, maintaining, and monitoring the performance of production quality code


Learning the complex Angi ecosystem and historical pricing paradigms in order to be a subject matter
expert on the data, analysis, and modeling





Who you are




Master’s degree in Statistics, Applied Mathematics, Economics or similar quantitative field and/or 7+ years of experience in:





Performing quantitative analysis, predictive analytics, mathematical modeling and/or machine learning

Proven record of working closely with senior leadership


Experience with price elasticity, pricing strategy, and pricing in a 2 sided marketplace


Demonstrating creative problem solving skills to inform decisions, improve outcomes, and deliver
transformation through data


Developing predictive models and analysis using R and/or Python


Interacting with data using SQL


Excellent verbal and written communications skills








We value diversity
We know that the best ideas come from teams where diverse points of view uncover new solutions to hard problems. We welcome and value individuals who bring diverse life experiences, educational backgrounds, cultures, and work experiences.
Compensation & Benefits: 





The salary band for this position ranges from $175,000-$230,000, commensurate with experience and performance. Compensation may vary based on factors such as cost of living.


This position will be eligible for a competitive year end performance bonus & equity package.


Full medical, dental, vision package to fit your needs


Flexible vacation policy; work hard and take time when you need it


Pet discount plans & retirement plan with company match (401K)


The rare opportunity to work with sharp, motivated teammates solving some of the most unique challenges and changing the world





#LI-Hybrid
Staff Researcher Machine Learning at Github 370E8D20 Ebc0 40B8 8280 1002A45B4Fe9

GitHub is looking for a Staff Researcher to join GitHub Next.
GitHub Next is Github’s advanced R&D team, tasked with building the future of software development.  We created GitHub Copilot, the first large-scale application of LLMs, and we want to continue leveraging the power of machine learning to revolutionize GitHub and hence the world-wide community of developers and creators who rely on it for their daily work. 
You will be working with other members of Next as well as colleagues from elsewhere in GitHub and Microsoft on providing machine learning solutions to these challenges. Our projects range from creating entirely new products like GitHub Copilot to integrating new ML-powered capabilities into existing GitHub surfaces, such as Copilot for Pull Requests.  The common thread is that our projects exist at the intersection of research and practice.
Responsibilities:

Participate in projects to integrate machine learning into developer tools.
Apply pretrained models to solve problems for software developers.
Conceive, design, train and deploy machine learning models.
Contribute to the day-to-day running of Next: participate in our reading group, interviewing new candidates, and disseminating research results.

Required Qualifications:

Strong coding skills and coding experience
Practical experience in machine learning development, deployment, and optimization with evidence of successful project completion in industry or academia
Demonstrated interest and experience in developing and improving developer tooling, such as libraries, frameworks, and IDEs

Preferred Qualifications:

Experience in training and deploying large language models (LLMs) with advanced techniques such as transfer learning, attention mechanisms, and regularization
M.S. or Ph.D. in Computer Science or a related field with relevant coursework and research experience in machine learning
One or more publications in top machine learning and/or natural language processing conferences, such as ICML, NeurIPS, ACL, etc.
Demonstrated interest and experience in developing and improving developer tooling, such as libraries, frameworks, and IDEs

 

Location: In this role, you can work remotely from anywhere in the United Kingdom or onsite in GitHub’s Oxford office.
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Vp Data at Cohere Health

Company Overview:
Cohere Health is illuminating healthcare for patients, their doctors, and all those who are important in a patient’s healthcare experience, both in and out of the doctor's office. Founded in August 2019, we are committed to eliminating wasteful friction patients and doctors experienced in areas with nothing to do with health and treatment. To that end, we build software that is expressly designed to ensure the appropriate plan of care is understood and expeditiously approved so that patients and doctors can focus on health, rather than payment or administrative hassles.
Opportunity Overview:
The technology group at Cohere Health has experienced rapid growth over the past three years. Each year, the team has doubled in size, and the group has grown from a small, tight-knit team to a large, diverse group of engineers and data scientists. We are seeking a leader to consolidate data engineering, data management, data science, and machine learning. The leader will foster greater cohesion between the functions and expand their capacity and capabilities to face the ambitious goal of eliminating unnecessary administrative burden from the US healthcare system.
Last but not least: People who succeed here are empathetic teammates who are candid, kind, caring, and embody our core values and principles. We believe that diverse, inclusive teams make the most impactful work. Cohere is deeply invested in ensuring that we have a supportive, growth-oriented environment that works for everyone. 
What you will do:

Lead the data engineering, data management, data science, and machine learning teams 
Execute a continual planning process that delivers dependable results
Foster a culture of curiosity and discovery
Develop an organizational obsession with delivering high-quality data insights efficiently and effectively.
Collaborate with cross-functional teams, including product, design, and operations so that the company's data asset delivers outsized returns. 
Manage and foster both formal and informal talent development activities.
Above all, strengthen the existing culture to make Cohere Health an employer of choice for top talent.  

Your background and characteristics:

PhD or Master's degree in quantitative science or data engineering, or a related field
A minimum of 10 years of experience in data science, with at least 5 years of experience in a leadership role
Strong experience with iterative delivery methodologies such as Agile or Scrum applied to data science or machine learning teams. 
Familiarity with R, Python, PyTorch, MLFLow, Spark, cluster technologies such as Kubernetes and EMR. 
At least 5 years experience with healthcare or payer technology
The ideal candidate will have a proven track record of building and leading teams in a high growth environment.

We can’t wait to learn more about you and meet you at Cohere Health!
Equal Opportunity Statement: 
Cohere Health is an Equal Opportunity Employer. We are committed to fostering an environment of mutual respect where equal employment opportunities are available to all.  To us, it’s personal.
 
 
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#BI-Remote
Data Scientist Forest Ecosystems at Planet

About the Role:  
We are looking for a passionate data scientist to join the Forest Ecosystems engineering team. We are on a mission to map, measure, and monitor the world’s forests using high resolution satellite imagery. Our team works with multi-sensor earth observations data, developing workflows that integrate measurements from Planet’s unique constellation with public data sources, including multispectral, LiDAR, and SAR data. We are developing object detection models to identify and count individual trees in high resolution imagery. This work will span spatial and organismal scales, counting both recently planted saplings and mature standing trees from sites around the world. You will contribute by developing consistent, scalable, and science-based instance segmentation methods using sub-meter satellite imagery. As a member of this team, you will have the opportunity to work with an experienced team of scientists and engineers, experiment with deploying your models at scale, and iterate with feedback from users and stakeholders. We are a small and growing team, with a highly collaborative culture, distributed remotely across USA and Canada. 
Impact You’ll Own:

Develop novel methods to count and delineate trees in satellite imagery
Collaborate with the team to iteratively build and test our suite of forest-related data products with end users, who are often focused on conservation and restoration
Implement models as efficient python code that can be deployed at scale
Document and organize your work to be transparent and repeatable  
Write external documentation, white papers and occasionally research papers

What You Bring:

PhD in forest ecology, environmental science, forestry or related
Solid understanding of machine learning or image analysis
Research or professional experience deriving tree attributes from sensor data
Fluency with geospatial technologies in python (e.g. GDAL, rasterio, shapely, etc)
Proficiency with Python in a Linux environment
Experience with version control and Git
Excellent technical communication and documentation skills

What Makes You Stand Out:

Experience training and deploying deep learning models
Experience with cloud compute and storage

Benefits While Working at Planet:

Comprehensive Health Plan
Wellness program and onsite massages in specific offices
Flexible Time Off
Recognition Programs
Commuter Benefits
Learning and Tuition Reimbursement
Parental Leave
Offsites and Happy Hours
Volunteering Benefits

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Senior Forecast Modeling Manager at Guild Education

Guild is hiring a Senior Forecast Modeling Manager to scale the efficiency of a growing team within Financial Planning & Analytics. In this position, you’ll play a key role in building out and leading a team that uses data & analytics to effectively budget and forecast the client’s education benefit program.
In particular, we’re looking for a team member who can thrive in detecting patterns and themes, supporting a client-facing team that operates in a complex, high-touch environment. In this role, you’ll have a unique opportunity to work on innovative challenges that will allow us to mature our budgeting and forecasting processes, deepening relationships with clients.
As a Senior Manager: Forecast Modeling, you will:

Lead and build a team of analysts and data scientists to handle budgeting and forecasting for Guild's Employer Partners
Build and own scalable modeling solutions, toolkits, best practice documents, and a consulting approach that can be applied across Guild partner base
Manipulate and analyze complicated data sets, partnering as needed to improve data quality and infrastructure
Influence critical business decisions by providing insights supported by reporting and analytics
Partner cross-functionally with our Data Engineering, Product, Technology, and other teams to support business needs
Lead ongoing experimentation with modeling and data science methodologies 
Produce insights, analyses, and recommendations to help employers understand drivers of spend and the impact of changes in student behavior over time, as well as these changes on revenue

You are a strong fit for this role if you have:

5-7+ years of total experience in an analytics, data science, financial planning & analysis
Experience leading technical and/or analytical teams in a fast paced environment
Exceptional problem solving, analytical, data visualization, and project management skills
Strong ability to identify the most significant metrics for a given business objective and translate analyses into tangible recommendations for sales and client services teams, working cross functionally to achieve shared objectives
Comfort presenting financial data to senior team members internally and / or at client organizations with an ability to influence perspectives via data-driven storytelling
Ability to execute quickly with high attention to detail in a fast-paced, dynamic environment
Expertise in model development, maintenance and tuning (including logistic regression, random forest, time-series forecasting), and at least one coding language (R, Python, etc.)
Fluency in SQL, Tableau (or other data visualization tool), and Excel

We feel passionately about equal pay for equal work, and transparency in compensation is one vehicle to achieve that. Total compensation for this role is market competitive, including a base salary range of $132,000 - $165,000, as well as company stock options. 
 
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Data Scientist at Focuskpi

FocusKPI is seeking a Data Scientist to enable deep media insights through advanced analytics for our client, one of the largest retailers/e-commerce companies in the U.S..
Work Location: Remote in the U.S. Duration: 6 months contract with potential for extension/conversion
Responsibilities:
Perform hands-on coding to retrieve and analyze large datasets using Python and SQLIntegrate disparate data sources and leverage state-of-the-art analytics best practices to deliver integrated actionable insights to partners and stakeholdersManage and streamline data extraction process with great attention to detailsAssess the potential usefulness, validity, and rigor of new data sourcesWork with cross-functional team to ensure that the quality of the data are of the highest standardHelp with media mix models to connect the impact of marketing tactics and business short-term and long-term outcomes
Qualifications:
Master’s degree in statistics/mathematics, engineering, computer science, economics, or related field3+ years of industry experience in data, analytics, data science roleProficient coding skills (SQL/Python/R)Deep knowledge on relational database capabilities and experience with big data technologies (Hive/Hadoop)Proficient BI/BA data visualization tools (Tableau, PowerBI, ThoughtSpot, Looker, etc)Experience with cloud technologies such as GCP, AWS, AzureExperience in integrating, structuring, and analyzing large amounts of data from diverse sourcesStrong project management skills and attend-to-detail documentation skills.Strong written & verbal communication with the ability to communicate complex technical topics clearly to a range of audiences and to ‘tell a story’ that provides insight into the businessPassion for working in a fast-paced agile environment.A collaborative mindset and sense of curiosity
Preferred Qualifications:
PhD degree in statistics/mathematics, engineering, computer science, economics, or related fieldExperience with predictive modeling algorithms and optimization techniquesExperience applying statistics to business problemsExperience with advertising, measurement, and/or digital marketing analyticsExperience with advertising technology platforms Ad servers, DSPs, DMPs, etc.
Thank you!
FocusKPI Hiring Team
Founded in 2010, FocusKPI, Inc. (FocusKPI) is a data science and technology firm specializing in predictive analytics practice and methodologies. FocusKPI is a US company headquartered in Silicon Valley, California with an East Coast office in Boston, Massachusetts.
Data Scientist Experimentation at Focuskpi

FocusKPI, Inc. is looking for a Data Scientist (Experimentation) to work for our client. Work Location: RemoteDuration: 6 months, with potential for extension and conversion.Requirements:
Engage with stakeholders to understand strategic challenges, understand their needs, cross-question them to avoid assumptions, and proactively recommend intelligent insights to solve the unanswered questions throughout the engagementDevelop, Design, and support interactive Tableau Dashboard reportsWork with Data Visualization Support towards better storytellingDeliver reports in an agile environment and timely mannerIdentify ways to enable analysts and data scientists to experiment faster and more rigorously than today.Put in place tables and dashboards to speed up the experimentation process.Measure the impact of our experimentation center of excellence strategy, designing and analyzing the launch of experimentation tools and frameworks.Assess the current state of experimentation through analyses and needs assessments.Foster a world-class analytics culture through education and the creation of self-service tools to make a lasting change in how your analysts use experiments to make decisions
Qualifications:
Collaboration with other team members and stakeholders is a key strengthStrong proficiency with SQLSome Databricks (creating notebooks and pipelines) or different tool experienceAbility to Prepare documentation and specifications, as and when necessaryExperience with A/B testing is required3+ years of experience with TableauExperience with statistical programming languages (R or Python). Previously worked in global teams and high-growth companiesAn understanding of the SaaS development, business model, and metricsAre an active member of the broader analytics and data science communityStrong ability to communicate.Explaining complex concepts to diverse audiences and crafting compelling stories
Thank you!
FocusKPI Hiring Team
Founded in 2010, FocusKPI, Inc. (FocusKPI) is a data science and technology firm specializing in predictive analytics practice and methodologies. FocusKPI is a US company headquartered in Silicon Valley, California with an East Coast office in Boston, Massachusetts.
Manager Senior Manager Data Science at Forward Financing

As Manager/Senior Manager, Data Science, you will lead the execution of building and deploying our predictive models. This is an exciting opportunity to get on the ground floor of a team at a growing company, and to guide the direction of how we build our data science capabilities. The ideal candidate has past technical experience building, deploying and monitoring credit risk predictive models, and can provide a vision of the tools and processes we should use in every stage of the modeling process. You will be joining our Analytics department, and report to the Director of Analytics and Data Science.
We have a modern analytics stack (Snowflake+Fivetran+DBT) that our Analytics Engineering and Business Intelligence teams use to centralize, clean, transform and model all of our data. We have access to many third-party datasets, in addition to our internal proprietary data. You will collaborate closely with the Analytics team to build datasets that will be used by data scientists to build models. You will also collaborate closely with our Technology team to deploy models into our applications. Our company is putting a lot of resources into automating our business, and you will play a key role in helping drive this initiative forward.
In this role you will:

Identify, evaluate, and implement data science tools and processes
Hire and manage data scientists
Collaborate with data scientists, analytics engineering and technology to build and deploy predictive models
Monitor and tune existing models
Collaborate with leadership to identify predictive model use cases

Requirements:
(Even if you don’t check every box, but see yourself contributing, please apply.)

7+ years of technical data science experience
Experience creating credit risk predictive models
Experience working with lending related datasets including: credit bureau, public records and transaction level bank statement data
Proficient in SQL
Proficient in a scripting language, such as Python or R
Strong project management and communication skills

Preferred: 

Experience as a people manager
Experience with Snowflake, Databricks, Tableau and DataRobot
Real World Data Rwd Scientist at Tempus

Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
With the advent of genomic sequencing, digital imaging, and techniques for large-scale clinical data processing, we have powerful new weapons in the data-driven fight against cancer. We’re on a mission to connect an entire ecosystem to redefine how genomic and clinical data is used for evidence-based medicine.
On the Real World Data Analytics (RWDA) team at Tempus, we are data-savvy scientists helping Key Opinion Leaders in academia and the research community interrogate the real-world dataset for novel insights. We work directly with the Tempus Medical Sciences Team and oncology research leaders to understand their goals and analyze Tempus data to answer their scientific questions.
We are seeking a highly motivated and capable Data Scientist with extensive experience working with clinical research pipelines applying biostatistics and epidemiology knowledge to observational health data. Top candidates will have knowledge of clinical and molecular oncology and a demonstrated history of consulting in clinical research.
What you’ll do
As part of the external data science team at Tempus, you’ll be on the front lines of our collaborations with external partners, helping them apply cutting-edge data science techniques to unique cancer datasets. Your work will be part of the foundation of the next layer of research questions: you will be responsible for performing rigorous, creative analytical studies on real-world clinical and molecular data, and for communicating results and scientific findings on a regular basis, using appropriate communication and visualization tools commonly used in clinical research.
Requirements:

Advanced degree (Masters or PhD) in biostatistics, epidemiology, or a related field or 3+ years experience working with genomic and clinical data in cancer
Experience working with statistical modeling methods
Proficiency in R programming
Experience working with observational clinical data

Strong project management skills  

Demonstrated ability to communicate technical concepts to non-technical stakeholders
Collaborative mindset, an eagerness to learn and a high integrity work ethic

Nice-to-have:

SQL
Computational biology techniques and tooling (i.e. Bioconductor)
Knowledge of next-generation sequencing technologies

 
#LI-GL1
#LI-Hybrid
#LI-Remote
#LI-Onsite
Staff Machine Learning Scientist Cardio at Tempus

Passionate about precision medicine and advancing the healthcare industry?
Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.
What You Will Do:

Analyze and integrate large diverse clinical, molecular and imaging datasets to extract insights, and drive research opportunities.
Design and prototype novel analysis tools and algorithms for predicting patient outcome and treatment response.
Collaborate with product, science, engineering, and business development teams to build the most advanced data platform in precision medicine.
Interrogate analytical results for robustness, validity, and out of sample stability.
Document, summarize, and present your findings to a group of peers and stakeholders.
Provide technical leadership & expertise across multiple modeling projects.

Required Qualifications:

PhD degree in a quantitative discipline (e.g. computer science, biomedical informatics, machine learning, statistics, computational biology, applied mathematics, physics, or similar).
3+ years of relevant industry or postdoctoral experience.
Outstanding analytical and problem solving skills, with a particular focus on understanding the intricacies of multi-modal medical data sets.
Experience working with clinical, electrocardiography, genomic, or imaging data.
Expert-level experience with supervised, self-supervised and unsupervised machine learning algorithms, such as: regression, generative modeling, deep neural networks, gradient boosting, non-linear low dimensional embeddings and clustering.
Proficient in Python and SQL.
Experience with machine learning frameworks such as TensorFlow or PyTorch.
Strong programming skills.
Thrive in a fast-paced environment and willing to shift priorities seamlessly.
Experience with communicating insights and presenting concepts to diverse audiences.
Team player mindset and ability to work in an interdisciplinary team.
Goal orientation, self motivation, and drive to make a positive impact in healthcare.

 Preferred Qualifications:

Strong peer-reviewed publication record
Familiarity with cloud computing services
Experience building machine learning based models towards cardiovascular outcomes
Experience working with structured and unstructured Electronic Health Records
Experience with signal processing and modeling ECGs
Familiarity with natural language processing 
Experience in agile environments and comfort with quick iterations.

#LI-SH1
#LI-Hybrid
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#LI-Onsite
Director Ii Data Science Product Design Modeling Property General Liability at Liberty Mutual

The Product Design and Modeling team has two openings for a Director II, Data Science, who will each lead a team responsible for driving pricing and non-pricing sophistication in the US Design team separately for the Property and General Liability (GL) lines of business. These managers will report directly to the Package & WC Design Lead and will collaborate with global teams in Product Design and Modeling, including Complex Components, Demand Modeling, and Pricing Sophistication.
The positions are responsible for the following:
Building complex models that lead best-in-class new business pricing sophistication 
Leading the project and pricing management of the Property or GL line of business
Developing a high-performing pricing modeling team
This level reflects broad knowledge of Business Lines products, actuarial & data science techniques, and the application of those techniques for the Property & GL lines of business, separately.
Responsibilities: 
Develop expertise in Property or GL products in self and team as well as understanding of relationship with BOP products
Build complex models that lead best-in-class new business pricing sophistication
Collaborate with Economics team to understand product performance, investigate gaps and drive for additional accuracy in pricing models
Explore and utilize advanced modeling techniques (e.g., machine learning techniques such as Elastic Nets); collaborate with the Office of Data Science, and partner teams in Product Design and Modeling and Global Risk Solutions(Commercial Lines) to develop and align on best practices
Collaborate with Delivery, Solutions, and Underwriting Effectiveness teams to help implement new pricing programs
Provide thought leadership on the pricing strategy of Property or GL and how they support the BOP line of business
Lead the project and pricing management of the Property or GL line of business
Understand the competitive marketplace, business issues, and data challenges to deliver actionable insights, recommendations, and business processes
Develop a high-performing pricing modeling team
Job Specifications:
Reference:  2022-47152
Category: Data Science
Primary Location: Remote
Additional Locations: Boston, MA; Seattle, WA; 
Schedule: Full-Time
Salary: USD-$172,900.00-–-$227,500.00-/-Year
Education Level: 
 Travel: As Needed
Solutions Data Science Internship at One Concern

About One Concern
One Concern brings disaster science together with machine learning for better decision-making. We quantify resilience from catastrophic perils, empowering leaders to measure, mitigate, and transfer risk. We believe that by pioneering cutting-edge science, we can make disasters less disastrous and, ultimately, build planetary-scale resilience.


The Role 
One Concern is growing rapidly, and we are looking for a passionate, mission-driven Solutions Data Science Intern to join our team. In this role, you’ll work with our solutions team to build data analytics and statistics visualizations corresponding with client requests. This is a full-time internship for a period of two to three months with the possibility of converting to full-time employment.


What You'll do 

Collaborate with an interdisciplinary team of data scientists on cross-functional projects, interpreting data, and translating into actionable insights.
Support an international team of researchers in designing and testing supply chain models.
Work with and support domain experts and data scientists in different projects.
Query and analyze large datasets in accordance with client requests.
Perform data sanity checks to ensure data integrity and summarize data to provide meaningful insights.
Build easily digestible and reproducible visualizations for the data summaries.



Qualifications and Experience 

Pursuing Ph. D. or MS in computer science, statistics, mathematics, or related fields. 
Experience in supply chain risk analysis and operations research. 
Network analysis background highly desirable
Exposure to coding, Python or MATLAB proficiency highly preferred



Nice to Haves 

SQL or Snowflake experience
Domain knowledge of natural disasters
Experience in large scale simulations


Compensation will be competitive with the market for this position and will include equity consideration. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, natural origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
Staff Data Scientist at Bolt

Responsibilities

Build production ready data mining and big data analytics algorithms and pipelines; your models will be the engine that powers all online commerce through Bolt
Conduct data analysis to determine which policies we adopt and help inform strategic growth
Build statistical models, data pipelines, data mining, data analytics, and production ready services to serve offline and live traffic
Work with other teams at Bolt to engineer data models and extract data insights that help improve Bolt business

About you

Passion to improve e-commerce businesses
Strong communication skills in a cross-functional team
Unrelenting focus on impact
Ability to formulate business problems into quantitative objectives and developing methodological solutions

Requirements

MS/PhD in math, statistics, computer science, or other quantitative field
5+ years of experience in developing ML/statistical models in an applied setting
Knowledge of statistical concepts and techniques such as statistical inference, causal inference, or predictive modeling
Knowledge of data mining, and big data analytics techniques
Experience with big data processing pipelines and orchestration tools
Mastery in SQL or other big data processing languages
Experience with one of the programming languages such as Python, R, Java, Scala

Preferred

Experience with big data technologies such as BigQuery, Spark, Dataflow, Apache Beam, Pubsub, Cloud Functions, EMR, S3, Glue, Kinesis Firehose, Lambda

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