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
Base Compensation Range
$150,000$205,000 USD

Compensation & Benefits 

  • Competitive cash compensation
  • A piece of the pie (in the form of equity)
  • Comprehensive health plans
  • Generous PTO
  • Future focused 401k match
  • Generous parental and caregiver leave
  • Our core values are more than just a poster on the wall; they’re tangibly reflected in our work


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