nathansutton/data-science-job-descriptions huggingface dataset:
Community Marketing Data 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 return to an office as they reopen (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.
Does the challenge of scaling a fast-growing company by powering it with data and reporting excite you? Using your business instincts and technical creativity, you will build tools to automate reporting and produce insights to allow marketing leaders quickly see how our programs are performing. We're growing quickly, so you'll need to develop the processes for delivering data to colleagues across the marketing organization. You'll be a phenomenal fit for this role if you enjoy finding patterns amidst chaos, making quick decisions, and aren't afraid of being wrong.
Your future team
You will sit on our Marketing Analytics team and partner with our Community & Customer Advocacy Marketing team. The Atlassian Community is a growing group of Atlassian power users who participate in our online forum, attend events and promote our products.
What you'll do
Define and report on funnel metrics to monitor the health and growth of the Community.Use data to understand the role the Community plays in customer experience and the value it has to the Atlassian business.Build measurement frameworks that identify and move customers from engaged users to potential champions to brand advocates.Collaborate with our Community web analytics and Machine Learning teams to experiment and personalize the web experience.
Your background
3+ years of experience in data and analytics fieldsAdvanced proficiency in SQLProficiency with data visualization best practices and tools such as TableauKnowledge of marketing measurement techniques (attribution, A/B testing, web analytics) and experience with customer engagement metrics (MAU, retention, CSAT)Ability to bring multiple data sources together to define metrics and create compelling/accurate stories about business performanceExperience collaborating with stakeholders, translating data-driven insights into decisions and actions
Senior Data Scientist Drug Utilization Forecasting at Hophr

POSITION SUMMARY:

• Identify opportunities to modernize an actuarial framework with data science model-based solutions.

• Determine analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes.

• Develop complex algorithms and statistical predictive models.

• Extract qualitative and quantitative relationships (i.e., patterns, trends) from large amounts of data using statistical and data mining tools.

• Work alongside the data engineering team to assess data quality, clean and organize data, optimize data flow and organization of code, production, and scale models.

• Apply analytical rigor and statistical methods to analyze large amounts of data using advanced statistical techniques.

• Develop an advanced understanding of the current forecasting system, stakeholders, and work products, and identify opportunities for enhancements and support of new initiatives.

• Create a new system to measure the forecast accuracy of current systems.


REQUIRED QUALIFICATIONS:

3 or more years of relevant analytic experience
3 or more years of experience programming using R, Python, SQL
3 or more years of experience with dimension reduction, machine learning, and statistical algorithms



PREFERRED QUALIFICATIONS:

Advanced knowledge level for SQL.
3+ years of experience applying modern machine learning techniques to build predictive models for both classification and regression problems using python libraries such as sci-kit-learn, ml-lib, xgboost, Keras, etc.
3+ years of experience with general linear models, including regression techniques, ensemble models, etc.
3+ years of experience coding in Python, including PySpark, and Pandas.
Experience with time series forecasting and causal modeling techniques.
Knowledge of full model development life cycle including EDA, feature engineering, data visualization, model development and deployment, forecast accuracy, model monitoring, and model drift.
Experience with the pharmaceutical or other healthcare domains with large administrative claims datasets including their associated code sets, terminologies, and ontologies.
Senior Data Scientist Care Management at Hophr

Responsible for Optimizing Care Management Experience.
• Use strong programming skills to explore, examine and interpret large volumes of data in various forms.

• Performs analyses of structured and unstructured data to solve multiple and/or complex business problems utilizing advanced statistical techniques and mathematical analyses and broad knowledge of the organization and/or industry.

• Develops and/or uses algorithms and statistical predictive models and determines analytical approaches and modeling techniques to evaluate scenarios and potential future outcomes.

• Collaborates with business partners to understand their problems and goals, and develop predictive modeling, statistical analysis, data reports, and performance metrics.

• Develops and participates in presentations and consultations to existing and prospective constituents on analytics results and solutions.

• Interacts with internal and external peers and managers to exchange complex information related to areas of specialization.

• Use strong knowledge of algorithms and predictive models to investigate problems, detect patterns and recommend solutions.


REQUIRED QUALIFICATIONS:

3+ years of relevant analytic experience.
Experience programming using R or Python.
Experience in SQL.



PREFERRED QUALIFICATIONS:

Demonstrates strong ability to communicate technical concepts and implications to business partners.
Understands the healthcare industry, specifically Care Management or health programs.
Anticipates and prevents problems and roadblocks before they occur.
Strong knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources.
Demonstrates proficiency in most areas of mathematical analysis methods, machine learning,
statistical analyses, predictive modeling, and in-depth specialization in some areas.
Marketing Analytics Data Science Senior Manager at Self

About The Role
As a Marketing Analytics & Data Science Senior Manager focused on acquisitions, channel strategy, life cycle marketing and marketing spend optimization, you’ll be responsible for coming up with data driven strategy and recommendations to drive growth across multiple products (Credit Builder, Cards, Marketplace, Rents and Bills, etc.) 
This role will report to the Director of Marketing Analytics.
Detailed Responsibilities:

Drive higher acquisitions by continuously providing data driven insights
Manage and mentor a high performing team of analysts to deliver high quality projects in a timely manner
Collaborate with cross-functional leaders and teams to manage projects and drive growth
Help the team to create impactful and intentional analyses and reports. 
Assess competitive landscape and leverage insights to drive A/B experiments.
Define how to measure success across various teams by creating metrics and KPI’s in partnership with the Marketing team
Define channel strategy and leverage marketing mix models to attribute customers to channels accurately and optimize spend across channels, driving down CPA while increasing originations
Help improve outcomes for Builders (customers) through segmentation, engagement analysis and experimentation

 
Ideal Candidate:

You are an experienced Analytics leader who excels at leading and growing a team of analysts. You excel at enabling your team to uncover insights to explain business performance, hit targets and timelines, and identify areas of opportunity to grow the business.
You have a successful track record of developing people and consider yourself a player coach
You have at least 5 - 7 years of Marketing Analytics and Data Science experience
You have at least 2 years of people management experience
You have experience with techniques such as A/B testing, and quasi-experimentation such as difference in differences, time series analysis, etc.
You are high skilled at SQL and have good knowledge of various statistical modeling techniques
You finish the work you start, and are comfortable communicating your insights to stakeholders at every stage of the business
Bachelor’s degree in Statistics, Finance, Economics or related analytical field and/or extensive industry experience (Master’s Preferred)
You have: Exceptional communication and presentation skills; Ability to work both independently and on a team; Strong problem solving and strategic thinking skills


You are: Results oriented, Self-motivated, Humble and proactive about asking questions
Principal Data Scientist at Pagerduty

Why We Need You:
As a Principal Data Scientist, you will be responsible for identifying, scoping, and delivering features with a focus on data science and machine learning. You will anticipate data and science-related bottlenecks, suggest escalation and investment wherever necessary, communicate immediate and long-term technical as well as strategic solutions and trade-offs, and will possess an excellent capacity to manage time. In addition, you will demonstrate emotional intelligence as you navigate stakeholder relationships championing data science and machine learning in the organization. If you are technically savvy, innovative, and excited about fostering an environment amongst our engineers that helps create avenues for success and learning, then this is an excellent opportunity for you.
 
How you contribute to our vision: Key Responsibilities

Build data-driven solutions to solve business-critical problems across multiple domains 
Work both independently and collaboratively with other data scientists, product managers, engineers, and designers to solve complex problems that deliver business value
Drive and Influence leadership to drive more data-informed decisions
Provide guidance, technical leadership, and mentoring to other members of the team
Proactively recommend improvements and new approaches addressing potential systemic pain points and technical debt

 
Minimum Requirements

Graduate degree in computer science, statistics, mathematics, or related quantitative field.
You have 8+ years of experience using machine learning for building data-driven product solutions for large-scale systems.
Hands-on experience in Python, SQL, and other related tools
Have an entrepreneurial mindset to drive research projects to completion with minimal guidance.
Strong ability to justify technical prioritization and communicate scientific work in a clear and effective manner to stakeholders, other engineers, and Product
Experience working with Engineering teams ensuring a timely delivery
Ability to articulate difficult technical nuances to different audiences 
Passionate about the field of data science and creating impact in the organization driving strategic data science ROI discussions
Data Science Team Lead at 15Gifts

About the role
We are looking for an excellent data science team lead with the drive and enthusiasm to manage, mentor and inspire our team of data scientists.
Data science is at the heart of what we do, from our recommendation engine and our greenfields machine learning projects to our Bayesian experimentation and optimisation. This is a great opportunity to play a crucial role in guiding and scaling our data science team as we move into a period of investment and growth.
We work in an AWS, snowflake, dbt, looker, python and fivetran stack and you would ideally be comfortable with these (or similar) and have a strong background and expertise in machine learning, programming and statistics. You should also be able to demonstrate a deep understanding of how these and other techniques can be applied to business problems and generate value.
As our data science team lead you will need to be comfortable managing people and bringing out the best in them, confident advocating for your team when required and enjoy fostering best practices. You will also be responsible for planning and managing an internal data science roadmap as well as executing this plan.
You will also need to be a part time individual contributor - and be confident taking a project brief and drawing out requirements, designing mvp solutions and getting sign off with the various stakeholders. Combining this with leading a team you will need to be adept at managing your time to execute the plan and/or supporting others in the team to do so.
We are looking for someone who is a self-starter, with the ability to see the big picture and understand how our data points are connected. We would like you to use your excellent communication skills to simplify concepts and explain them to others, and be comfortable liaising with people from all levels of the organisation whilst translating their needs and wants into clear requirements.
The successful candidate will join our fast growing and dynamic data team and work alongside our data engineers, analytics engineers, and customer analysts to provide the data products and insights which make a difference across the business.
To succeed in this role you will need to manage and mentor a high performing data science team which designs, creates and maintains intelligent data products and drives measurable business value.
Sr Data Scientist Ads Experimentation Analytics at Reddit

We are looking for a senior data scientist to be a part of the Ads Data Science team. You will work closely with product managers, engineers, and data scientists to up-level the experimentation capabilities of the ads organization. You have a strong understanding of experimentation, are not afraid to challenge the status quo, and thrive in a cross-functional environment.  
Reddit is continuing to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.
Responsibilities:

Elevate the experimentation practice for the Ads org by creating the right processes, templates and tools catered for ads use cases.
Lead an experimentation council that can approve/guide experiment designs for various product launches.
Explore new experiment designs/techniques such as small sample enhancements, Bayesian approaches, causal inference methodologies, dosage response studies, staggered experiments etc and apply them successfully for complex experiments on the ads side of the business.
Liaise with the centralized experimentation team in building infrastructure for budget split experiments and multi-cell experiments.
Guide various ads product teams in understanding network effects and novelty effects when running experiments.
Track and own the experiment calendar for the ads org. Run biweekly experiment review discussions.
Create frameworks for making metric trade-off decisions, especially when they span multiple organizations. An example is ads vs consumer metric tradeoffs.

What We Can Expect From You:

Master’s or PhD degree in a quantitative major (e.g., mathematics, statistics, economics, finance, computer science). 
2 years of experience with experimentation, preferably for a consumer-facing service/app.
5+ years of experience in quantitative/modeling roles.
Proficiency with statistical analysis and programming languages (Python, SQL).
Understanding of experimentation and causal inference analyses.
Experience with digital advertising is preferred, but not required.
Sr Data Scientist Analytics Growth Retention at Reddit

We are looking for a results-oriented and strategically minded Product Data Scientist to work with our Growth team as Reddit expands its user base and deepens user engagement. In particular, you will be focused on understanding what brings new users to Reddit, what drives Reddit users to keep coming back, and how to transform new user experience. Your work will be critical in how Reddit delivers personalized experiences and nurtures deeper connections between people and their communities. 
You will work side by side with a world-class org of Engineering, Machine Learning, Community Operations, Product Management practitioners who work together to create a variety of capabilities for Reddit to be more successful in its decision-making and product creation. As a Sr. Data Scientist, you will be influential in product prioritization and strategic direction. In this process, you will be exposed to a variety of new techniques in experimentation, machine learning, and exploratory analysis.
Reddit is continuing to grow our teams with the best talent. We're completely remote friendly and will continue to be after the pandemic.
How You’ll Have Impact:
Understanding and identifying the levers to create a successful first experience and to deepen user engagement are pivotal to accelerate Reddit’s growth. You will understand how existing features deliver value to our users in order to uncover new opportunities and influence future strategic bets and product vision.
What You’ll Learn:
You will drive insights in improving Reddit’s onboarding and early retention for a global and fast-growing user base through analyses and experimentation. You’ll be an expert on what people are looking for in online social communities, why they come to Reddit, and how we can create an experience that supports our users’ needs. 
What You’ll Do:

Partner cross functionally with Eng and Product leads to help define and execute Retention’s roadmap and initiatives
Become the analytical expert through exploratory and strategic analyses on onboarding intent and roadblocks and longer-term new user retention levers to influence product roadmaps
Generate actionable insights and opportunity sizing to steer product priorities and execution
Design and evaluate A/B tests for product feature experiments to determine the effectiveness of product strategy
Define team metrics and goals and work with the Data Warehouse team to create ETLs (extract/transform/load) and reporting dashboards

Who You Might Be:

6+ years of experience in quantitative analytical roles, preferably for growing at-scale consumer products outside the US
Proficiency with relational database (e.g., SQL)
Familiarity with statistical analysis and programming languages (e.g., R / Python)
Results-oriented with a strong customer and business focus
Entrepreneurial and self-directed, demonstrated ability to innovate and bias toward action in fast-paced environments.
Ability to communicate and discuss complex topics with technical and non-technical audiences
Ability to tackle ambiguous and undefined problems
Previous experience with product growth preferred
Senior Data Scientist at Samsara

About the role:
The Samsara AI team builds end-to-end machine learning and computer vision solutions for our customers as well as core ML infrastructure for Samsara. As a Senior Data Scientist you will be a science leader and key contributor in building core models and predictive techniques for use in building and understanding products. You will work closely with other scientists as well as full-stack, firmware, and platform teams to deliver core infrastructure, services, and optimizations.
This role can be office-based or fully remote in the US and Canada.

In this role, you will: 


Build and improve the accuracy of ML/CV models, including retraining and optimizing open-source models to solve Samsara-specific problems 
Work with petabyte-scale data from Samsara camera and sensor devices to develop new models
Research, adapt, and apply cutting edge techniques in CV and deep learning
Optimize models for inference on the backend and/or on edge devices
Partner with our hardware teams to design devices for optimal performance and cost
Stay connected to industry and academic research and adopt novel technology that suits Samsara’s needs
Champion, role model, and embed Samsara’s cultural principles (Focus on Customer Success, Build for the Long Term, Adopt a Growth Mindset, Be Inclusive, Win as a Team) as we scale globally and across new office

Minimum requirements for the role:

BS or MS in Computer Science or other quantitative field (e.g., Applied Math, Statistics)
5+ years experience as a Data Scientist, Machine Learning Engineer, or similar role
Proficiency in data modeling as well as SQL, Python, R, or a similar scripting language
Ability to distill informal or ambiguous customer and business requirements into crisp problem definitions
Proven ability to communicate verbally and in writing to technical peers and leadership teams with various levels of technical knowledge

An ideal candidate also has:

PhD in Computer Science or quantitative discipline (e.g., Applied Math, Physics, Statistics)
Strong functional knowledge of common tools like Jupyter Notebooks, AWS (e.g., EMR, Redshift, S3, Sagemaker)
Record of successful mentoring and development of junior team members
Experience working with large datasets using distributed computing (e.g., Spark, Hive)

#LI-Remote
Data Scientist at Token Metrics

Token Metrics is searching for a highly capable machine learning engineer to optimize our machine learning systems. You will be evaluating existing machine learning (ML) processes, performing statistical analysis to resolve data set problems, and enhancing the accuracy of our AI software's predictive automation capabilities.

As a machine learning engineer, you should demonstrate solid data science knowledge and experience.

A first-class machine learning engineer will be someone whose expertise translates into the enhanced performance of predictive models.


Responsibilities

Consulting with the manager to determine and refine machine learning objectives.
Designing machine learning systems and self-running artificial intelligence (AI) to automate predictive models.
Transforming data science prototypes and applying appropriate ML algorithms and tools.
Ensuring that algorithms generate accurate user recommendations.
Solving complex problems with multi-layered data sets, as well as optimizing existing machine learning libraries and frameworks.
Developing ML algorithms to analyze huge volumes of historical data to make predictions.
Stress testing, performing statistical analysis, and interpreting test results for all market conditions.
Documenting machine learning processes.
Keeping abreast of developments in machine learning.



Requirements

Bachelor's degree in computer science, data science, mathematics, or a related field.
Master’s degree in computational linguistics, data science, data analytics, or similar will be advantageous.
At least two years' experience as a machine learning engineer.
Advanced proficiency with Python, Java, and R code.
Extensive knowledge of ML frameworks, libraries, data structures, data modeling, and software architecture.
In-depth knowledge of mathematics, statistics, and algorithms.
Superb analytical and problem-solving abilities.
Great communication and collaboration skills.
Excellent time management and organizational abilities.



About Token Metrics

Token Metrics helps crypto investors build profitable portfolios using artificial intelligence based crypto indices, rankings, and price predictions. 

Token Metrics has a diverse set of customers, from retail investors and traders to crypto fund managers, in more than 50 countries.
Devrel Data Scientist at Hophr

POSITION SUMMARY:

DevRel (Developer Relation) Data Scientists are machine learning experts who are driven to make our users successful. Your goal is to amplify the usage, mindshare, and adoption of the client's and AI Quality best practices. By doing so, you have a positive impact on the ethical, transparent, and trusted adoption of AI. And to drive feedback back into the product teams and improve our offerings, you will work closely with product managers and software engineering teams.

As a DevRel Data Scientist, you’ll be exposed to a huge range of machine learning use cases from ridesharing to credit decisions, and supply chain management to Twitter sentiment analysis. You will also help support the company’s educational initiatives including creating AI Quality courses and engaging with the client's user community.


REQUIRED QUALIFICATIONS:

2+ years of DevRel experience or equivalent
Proficiency in developing, troubleshooting, and optimizing machine learning models in Python
Experience with model packages/frameworks such as XGBoost, LightGBM, Scikit-learn, DataRobot, H20
Experience with NLP and deep neural network frameworks such as TensorFlow and/or PyTorch
Strong understanding of data science workflows and architectures
Excellent organizational, communication, writing, and interpersonal skills
Ability to wear multiple hats with a “do whatever it takes” attitude
Master's degree or higher (or equivalent experience ) is preferred in the area of data science, computer science, statistics, or mathematics



RESPONSIBILITIES:

Develop a deep understanding of our user’s machine learning use cases and AI Quality goals
Leverage your machine learning experience and expert client's product knowledge to help our users optimize the usage of the company.
Create strong help content, quick starts, documentation
Create sample models for illustrating new machine learning and AI quality concepts
Help grow the client's user community and represent the company at AI/ML events
Work closely with the company's product management and engineering teams to align customer requirements to future versions and products
Data Scientist at Hophr

POSITION SUMMARY: 

The Clinical Analytics team creates innovative analytic tools to drive better healthcare outcomes. We’re currently seeking a Data Scientist to support the development and implementation of analytic capabilities that measure and enhance the value of integration of the company's products and programs. Responsibilities include developing advanced analytics, predictive models and machine learning/deep learning algorithms to identify care opportunities, prioritization of clinical recommendations, evaluation of program performance, and optimization of information delivery. The Data Scientist will collaborate with other data scientists and business partners and will participate in all phases of initiatives from exploration of clinical opportunities, development of solutions, to partnering with IT and business teams for implementation.



FUNDAMENTAL COMPONENTS:

Develops, validates and executes algorithms and predictive models to investigate problems, detect patterns and recommend solutions
Explores, examines and interprets large volumes of data in various forms
Performs analyses of structured and unstructured data to solve moderately complex business problems utilizing advanced statistical techniques, machine learning algorithms, and mathematical analyses
Develops data structures and pipelines to organize, collect and standardize data that helps generate insights and addresses reporting needs
Uses data visualization techniques to effectively communicate analytical results and support business decisions
Creates and evaluates the data needs of assigned projects and assures the integrity of the data
Explores existing data and recommends additional sources of data for improvements
Documents projects including business objectives, data gathering and processing, detailed set of results and analytical metrics



REQUIRED QUALIFICATIONS:

2 or more years of experience with complex data management and analytics
Strong knowledge of statistical methodology, predictive and inferential modeling, data mining and exploration and machine learning techniques
Experience using R and/or Python to manipulate large datasets and deploy quantitative techniques ranging from descriptive statistics to deep learning
Ability to write SQL code to extract, organize and aggregate data from various data sources (e.g. GCP, Hadoop, Netezza or DB2)



PREFERRED QUALIFICATIONS:

Understanding of health care industry and clinical research concepts
Demonstrates ability to clearly communicate technical concepts, results and implications to management and internal stakeholders
Senior Ml Engineer Sr Data Scientist at Hophr

You will be joining a best-in-class team on a trajectory of tremendous growth. We are a Series-B start-up, backed by top tier investors Canapi Ventures, FinVC Capital, and TTV Capital and we serve some of the largest names across various industries such as Intuit, Square, Affirm, Mission Lane, Petal, and others.

We are pioneering the behavioral analytics space, providing a new standard for collecting, translating and actioning on the real-time behaviors of digital interactions. Through a body of patented technology leveraging over a decade of scientific research and discovery in Human-Computer Interaction (HCI) to measure both customer Intent and Experience. For companies, this real-time behavioral data is used during the digital onboarding process to segment genuine from fraudulent customers, enabling them to maximize conversion, reduce false positives and stop sophisticated fraud.

Founded by 2 world-renowned PhDs, and led by a team of seasoned executives, we continue to make strategic key additions to our team to expand our product offerings and enter new verticals.

Come join our team!

We have a large and unique data set with a unique set of challenges. It has tremendous potential. We are looking for an experienced data scientist to join our team, and take our modeling and ML to the next level.


JOB RESPONSIBILITIES:

Research and develop ML learning models and technology to power the behavior-as-a-service platform
Collaborate with engineering and other teams to deploy models into production.



REQUIRED QUALIFICATIONS:

5 years experience delivering data science projects analyzing and modeling large scale-multi dimensional data, preferably in an industry setting
Proven knowledge in model evaluation, tuning and performance, operationalization and scalability of scientific techniques and establishing decision strategies
Hands on experience developing supervised and unsupervised machine learning algorithms (regression, decision trees/random forest, neural networks, feature selection/reduction, clustering, etc.)
Fluency in Python, especially the data scientific stack (Jupyter/Pandas/sci-kit-learn)
Working knowledge of relational databases (e.g. PostgreSQL), experience with Snowflake and/or Looker is a plus
Experience with cloud computing platforms (AWS, Azure, etc.)
Outstanding communication skills (verbal, written and remote)



PREFERRED QUALIFICATIONS:
You have worked in a fraud data team at a financial institution.
Senior Machine Learning Scientist at Thirty Madison

We believe that intelligent technology working alongside outstanding care providers is key to delivering timely, quality and affordable healthcare to patients with complex chronic conditions. We’re looking for a motivated senior machine learning scientist to join our growing machine learning team to deliver on that vision. This is your opportunity to have an outsized impact on helping doctors make better decisions, improve healthcare access, keep patients engaged in their care, and improve their health outcomes as part of our mission to reinvent healthcare.
What you’ll do:

Work with clinical and operational partners to define how ML can help clinicians and patients make better decisions and expand access to care and improve health outcomes
Collaborate with fellow scientists, product managers and engineers to develop and deploy ML systems within clinical and operational workflows
Own projects end-to-end from scoping to data gathering, feature engineering, model development, deployment and performance monitoring
Stay on top of recent developments in ML methods in the search, recommender systems, NLP, computer vision, and causal inference spaces

You should have:

MS/PhD in computer science, statistics or another quantitative field
5+ years of applied machine learning experience in an e-commerce or healthcare setting
Deep knowledge of the fundamentals of traditional machine learning and deep learning
Strong proficiency in Python, SQL, GitHub, scikit-learn, and at least one deep learning framework (PyTorch, TensorFlow, Keras)
Experience training and deploying models in a cloud computing environment
Ability to communicate machine learning concepts to non-technical audiences
Data Scientist New Grad at Figma

The Data Science team at Figma partners directly with our product and engineering teams to uncover insights, influence decision making, and apply a data lens to business problems critical to Figma’s growth. Our work is diverse and evolving. As a member of our team, you will have the opportunity to work on a wide range of technical challenges from data engineering, analytics, experimentation, and machine learning. We seek data scientists with strong coding and statistics fundamentals and who are excellent communicators among technical and non-technical audiences.
What you’ll do at Figma:

Collaborate with cross-functional teams including Product, Engineering, Research, Design, Sales, and Marketing to turn business questions into data problems
Evaluate experiments to measure the impact of product changes
Define and surface metrics to guide decision making
Communicate and document data logging and requirements
Build models to understand user behavior and predict growth
Provide thoughtful feedback to others on the team
Help grow Figma by interviewing candidates for teams across Data Science


We'd love to hear from you if you:

Are pursuing a degree in Statistics, Computer Science, Mathematics, Economics or other quantitative field (advance degree preferred)
Have at least one previous data science internship or relevant research experience
Are proficient with basic SQL 
Have experience with R, Python, or similar scripting language
Have firm knowledge around statistical methods and models
Have a self-starting approach along with strong communication and collaboration skills



In your first few months, you'll:

Work with an onboarding buddy to make your first edits to our data tables and dashboards
Start to build deep context and expertise in Figma's data and product
Deliver your first product analysis



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
Figma's engineering values
By the numbers: one year of remote work
Inside Figma: a Q&A with our 2021 interns and new grads
Data Scientist Product Community Team at Figma

The vision of the Figma Community is to move Figma from standalone design tools to an ecosystem and platform. Community is where our users share, explore, and gain inspiration from one another. We provide the support for creators to thrive with the power of the design community and take their design process to the next level. 
 
We’re looking for a senior data scientist who will take ownership of this team’s data projects and serve as a strategic partner to Product, Engineering, Design, User Research, and Marketing. In working with an independent product surface with a unique focus, your responsibilities would cover a broad set of work including exploratory analysis, experimentation, and model evaluation and improvement related to the content discovery experience. The ideal candidate will have a strong track record of using data to influence product teams and help them achieve their goals through both analytics and machine learning.
 
This is a full time role that can be held from one of our US hubs or remotely in the United States.
 
What you’ll do at Figma:

Design and evaluate experiments to measure improvements to UI and algorithms
Generate ideas to creatively leverage data for shaping future product roadmaps
Collaborate with engineering to leverage machine learning to improve relevancy of content on Community.
Drive democratization of data through creation of new datasets and tooling
Design and surface metrics to guide decision making
Collaborate with cross-functional teams including Product, Engineering, Research, Design, and Marketing

 

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

Degree in a quantitative field(Advanced degree preferred)
3+ years relevant work experience
Fluency in Python, R or similar scripting language
Proficiency in SQL
Experience in distributed data processing systems(Hive, Redshift, Presto, Snowflake, etc)
Breadth of knowledge around machine learning and experiment design, including A/B testing and content ranking algorithms
Excellent judgment and creative problem solving skills
A self-starting mindset along with strong communication and collaboration skills

 


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 

By the numbers: one year of remote work
Measuring the value of design systems
Figma’s Series D:  The Decade of Design
Figma's engineering values
Senior Climate Data Scientist at Openearth

APPLY FOR A JOB AT THE OPEN EARTH FOUNDATION
Please send your resume with a brief cover letter to HR@openearth.org. The cover letter is an important part of the application, it is your opportunity to highlight why you feel you would be a great addition to the team. 
Senior Climate Data Scientist:
Integrating our global climate accounting
Open Earth Foundation is a California-based research and deployment non-profit developing open innovative technology to increase planetary resilience and avoid a catastrophic climate crisis.
We are a diverse international team, working with a network of collaborators and partners globally (from the United Nations to cutting-edge startups) and always ready to have fun saving the world.
We are building  open infrastructure for the Paris Agreement, energy finance, biodiversity tracking, and impact solutions at the intersection of emergent technologies (ML, blockchain, Web3 technologies, IoT devices) and climate innovations.
We have funding, a network of international partners and a team of experts focused on Earth systems and digital innovation. Now we need Digital Avengers to help us on our planetary mission.
Your mission, should you choose to accept it:
As a senior climate data & policy scientist you will provide research, leadership and hands-on data management in our climate accounting technology programs. Your work will cover clima data expertise across Earth system science (particularly carbon budgets), international climate accounting (eg. GHG Inventories, UNFCCC process, and Paris’ Global Stocktake) and Non-State actor climate strategies (eg. corporate and city-scale accounting).
You will work directly with the Executive Director, be the top climate expert in a digital R&D lab with 5-10 members, and work on up to 4 different simultaneous climate data and accounting development operations; involving in-house work and managing multiple external collaborators.
The ideal candidate: passionate researcher on Earth system science and data
Responsibilities: manage, research, code, calculate, engage
Oversee all climate research, datasets, developments and deployments for the Open Climate project.Manage the climate science vision and mission of the Open Climate program, including for the independent climate accounting network  for the Global Stocktake, the Nested Climate Accounting spatial web simulator, the North American Energy Certification pilot, and model registry development for the voluntary carbon market. Supervise all climate prompts in the Open Climate Collabathon.
Tech & Data Abilities
Interpersonal skills: A time-zone management master, clear communicator, creative and curious, attention to detail
Qualifications
OEF is an Equal Employment Opportunity Employer. We support diversity, equity and inclusion in teams, and believe people should align their work with their purpose. 
Please send your resume with a brief cover letter to HR@openearth.org. The cover letter is an important part of the application, it is your opportunity to highlight why you feel you would be a great addition to the team. We look forward to hearing from you!
Data Scientist Infectious Disease Modeling at The Public Health Company

We are seeking an exceptional Data Scientist to help us build the company.
ROLE DESCRIPTION
In this role, you will be working as a founding member of the Data Science team focused on building infectious disease models to help businesses and governments better predict, prevent, and respond to infectious disease outbreaks. The world now understands the importance of rigorous modeling of infectious disease in the public and private sectors, and you will be part of the early team at PHC building the future of the field. Modern data streams (genomic, mobility, search, social, etc) and modern computational techniques allow us to design, fit, and test models of transmission that are both more accurate and more flexible than classical approaches. In this role, you will:

Work closely with the Engineering and Product teams to build scalable mathematical modeling products that enable disease prevention, prediction, response, and risk assessment.
Perform statistical analyses of model performance, robustness, and impact.
Present interpretation of results to internal/external and technical/nontechnical stakeholders.
Provide technical and scientific guidance and mentor junior colleagues.
Write appropriate documentation and tests to ensure code reproducibility and reusability.
Contribute to scientific publications, technical reports, conferences, and open-source libraries
Work with all levels within the company including executive leadership to bring high-performing, actionable models to end users

REQUIREMENTS


Graduate degree in an analytical field such as epidemiology, biostatistics, statistics, mathematics, machine learning, or computer science.

Experience creating, implementing, and applying models of infectious disease transmission (or of systems with similar dynamics).
Deep understanding of statistical modeling approaches.
Experience using R or Python, Github, and the command line.
Strong communication skills with an emphasis on the ability to explain scientific and statistical concepts clearly.
Availability for meetings in the mornings, Pacific Time.

NICE TO HAVE

Experience working with an external stakeholder (either collaborator or client) on a infectious disease mathematical modeling project
Experience working with large datasets (>millions of rows) such as mobility data, electronic health records, social media data, census data
Experience with phylodynamic methods, agent-based models, and/or machine learning
Experience with cloud computing platforms, workflow managers, and data visualization
Experience contributing to open source software

PHC is a startup company, with the attendant excitement, energy, and opportunity for growth that a startup environment entails. The team supports remote-first employment and candidates from anywhere in the US are welcome to apply.
Data Scientist at Array

Job Description
Insights from data power decisions at Array. This Data Scientist role will work with product, engineering, sales and design teams to understand and analyze data from all parts of our business. You will use data science to help improve adoption and usage of our existing products and create new products. Data Scientists at Array will have a tremendous opportunity to make an impact to the top line and bottom line of a rapidly growing company. 
Responsibilities

Understand how our business works and drive the vision for how we share analytics and insights with our users

Work with large and complex data sets to solve a wide-range of challenging problems using different analytical and statistical approaches


Work closely with product, marketing and sales teams to innovate products and features to generate new revenue streams

Design and implement quick proof-of-concept experiments to validate hypothesis and demonstrate viability
Own the full lifecycle of model development: ideation and data exploration, algorithm design and testing, algorithm development and deployment, as well as algorithm monitoring and tuning in production.
Clearly communicate insights and technical approaches verbally and in writing, including documenting analytical methodologies and other outputs appropriate for use by specialist as well as non-specialists
Ensure high degree of confidence in the data products including but not limited to developing QA/QC strategies to ensure they are production-ready

Essential Skills

Master’s or Ph.D. in a quantitative field such as statistics, economics, industrial engineering and operations research, applied math, or other relevant quantitative field
3-6+ years of experience designing models for product analytics using statistical and machine learning techniques. Experience in financial services preferred but not required
3-6+ years of experience using advanced statistical techniques for experiment design, model development and deployment. Must have multiple, robust examples of using these techniques to measure effectiveness of data driven insights to solve business problems on large-scale data sets
5+ years of experience with one or more programming languages such as Python, R, PySpark
Expert-level knowledge of SQL with strong data exploration and manipulation skills
Experience using cloud platforms such as GCP and AWS for model development and operationalization is preferred
Must have superb quantitative reasoning and interpretation skills with strong ability to provide analysis-driven business insight and recommendations
Excellent written and verbal communication skills; ability to work well with peers and leaders across data science, product, marketing, and engineering organizations
Creative problem-solver who simplifies problems to their core elements
Experience with credit, transaction or other types of financial data is a big plus