Principal Data Scientist

Job Description We are seeking a Principal Data Scientist to support the transition of data science models and data pipelines from an external consulting partner to an in-house team. This role will focus on both enhancing existing models and improving the underlying code and data infrastructure to ensure long-term maintainability, scalability, and clarity. Key Responsibilities

•  Take ownership of fragility and hazard models currently developed by a consulting firm and lead their transition in-house
•  Support the development of machine learning models currently being developed in-house
•  Evaluate and improve model performance
•  Refactor and enhance data pipelines and model code to be modular, maintainable, and well-documented
•  Establish and promote best practices for code architecture, version control, and code management
•  Collaborate closely with a core team of data scientists and a broader team of cross-functional partners
•  Communicate technical data and models to non-technical stakeholders and regulators to build trust and understanding in the methodology.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.

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https://insightglobal.com/workforce-privacy-policy/. Skills and Requirements

•  Strong experience in Python-based data science and model development
•  Demonstrated expertise in code architecture, software engineering practices, and maintainable pipeline design, in a cloud-based environment
•  Experience working with hazard, fragility, or risk models (e.g., infrastructure, environmental, or reliability contexts)
•  Proficiency with version control (Git) and collaborative workflows (e.g., pull requests, code reviews)
•  Ability to assess and improve legacy or externally developed codebases
•  Excellent communication skills Preferred Qualifications
•  Experience with the Palantir Foundry platform
•  Familiarity with PySpark and distributed computing.
•  Experience working with spatial-temporal datasets and geospatial packages such as Sedona, Geopandas, and Rasterio.
•  Experience transitioning models from consulting or external vendors into production environments One Day per month in Oakland Office