Senior Data Scientist

As an AI/ML Senior Data Scientist at Pie, you will play a crucial role in developing and enhancing data-driven AI/ML solutions to address business challenges. You will collaborate with the data science, data/ML engineering, and product teams to conceptualize and build innovative ML solutions, explore deep-learning and NLP techniques, and engineer novel features. Your work will contribute to making AI/ML a key component of how Pie operates, ensuring that commercial insurance is affordable and easy for small businesses. The ideal candidate will have a strong background in data science, experience in building NLP-based solutions, and proficiency in technologies such as PyTorch and cloud data warehousing.

• 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
• Collaborate with Product, Data Engineering, and MLOps teams in the entire Model Development Life Cycle from conceptualization to deployment
• Help conceptualize, design, generate and test hypotheses, construct features, build and validate models
• Leverage 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
• 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
• 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
• 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
• Industry experience within insurance or financial industries (preferred)
• Experience with Langchain, semantic indexing, vector database(s), implementation of open-source language models (preferred)
• Experience with design and development of Knowledge Graph (preferred)
• Experience with data processing frameworks and tools (preferred)

Bachelor's Degree required, Master’s Degree preferred

5+ years experience as a data scientist

3+ years experience in building NLP-based solutions

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

Communication & collaboration in an agile environment

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

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

• Competitive cash compensation
• Equity participation
• Comprehensive health plans
• Generous PTO (Paid Time Off)
• Future focused 401k match
• Generous parental and caregiver leave
• Discretionary bonuses based on company performance
• Hybrid or remote work options
• Equal opportunity employment
• Participation in the E-Verify program
• Commitment to protecting personal data