Senior Data Scientist at Pie Insurance

As an AI/ML Senior Data Scientist, you will work with Pie’s data science, data/ML engineering, and product teams to conceptualize, build and enhance data-driven AI/ML solutions to address business challenges–having the opportunity to immediately impact various business functions through your efforts. As Senior Data Scientist, you will also get to explore the frontiers of deep-learning, Natural Language Processing/Generative AI, along with supervised/ unsupervised/semi-supervised ML algorithms to build more elegant ML solutions, engineer novel features, and construct automated capabilities. Ultimately, you will help ensure that using AI/ML is key to how we operate, and as easy as Pie.
How You’ll Do It
Working collaboratively with our Product, Data Engineering and MLOps teams, you will be actively involved in the entire Model Development Life Cycle from conceptualization to deployment. You will help conceptualize, design, generate and test hypotheses, construct features, build and validate models–leveraging your deep-learning and NLP skills to develop language-based features, build semantic indexing, construct domain-specific corpus, fine-tune pre-trained models, and build foundation and/or generative ML solutions.
The Ideal Candidate Will Be Able to -

Understand analytics & modeling needs; build validated data pipelines to extract internal and external data, conduct exploratory analysis 
Build new high-signal features; build, strengthen, and validate robust AI/ML solutions
Develop and implement feature engineering strategies to extract meaningful features from raw structured data and text-based data to optimize model performance
Conceptualize, prototype, and implement Generative and Augmented AI solutions, leveraging LLM, Image processing, and deep-learning capabilities 
Work with both data engineering and analytics teams to find useful data sources; ensure data quality and consistency

The Right Stuff

Bachelor's Degree required, Master’s Degree preferred
5+ years experience as a data scientist 

Building and delivering data solutions for a company that uses data as a primary aspect of its business

3+ years experience in building NLP-based solutions
Technologies:

Hands-on experience with Deep Learning frameworks such as PyTorch
Cloud data warehouse experience
Experience writing reusable, OO ML functions in Python
Strong experience in writing complex SQL programming/queries
Exposure to one major SQL RDBMS or analytics database (Snowflake, Redshift, MySQL, Postgres, Oracle, SQL Server, etc.)

Deep experience in data wrangling:

Data extraction, transformation, and cleansing
Text pre-processing
Data profiling and visualization
Analytical prep-work for predictive modeling
Automated data validation
Managing and maintaining metadata and corresponding data dictionaries

Communication & collaboration in an agile environment:

Experience collaborating with data engineers, analytics, software engineers, product managers in delivering ML models and data products
Ability to work in a fast-paced, agile environment and handle multiple projects simultaneously

Strong problem-solving and analytical skills

Proven experience identifying opportunities to automate data wrangling and analytics tasks and workflow
Experience with end-to-end product development using machine learning algorithms and techniques, including supervised and unsupervised learning, classification, regression, clustering, and deep learning

Additional preferred skills:

Industry experience within insurance or financial industries
Experience with Langchain, semantic indexing, vector database(s), implementation of open-source language models
Experience with design and development of Knowledge Graph
Experience with data processing frameworks and tools such as Spark/databricks, Snowflake
Familiarity with data visualization tools such as Tableau, Power BI, Dash, or matplotlib