Staff Data Scientist
Gradient AIAI for company
Remote$160,000-195,000Lead
MassMutual Ventures
Centana Growth Partners
Sandbox Insurtech Ventures
Forte Ventures
BSC Capital Partners
Stonepoint Capital
Data & AI
About the role
TL;DR
Lead complex modeling and analytical projects with minimal direction, raising the bar for the data science team.
- •{"about_the_role": " Gradient AI is the decision-intelligence partner for the insurance industry, giving customers an advantage in how they make decisions by revealing risk others miss and translating it into stronger performance and real-world impact.
- •Our platform harnesses a vast industry data lake \u2013 tens of millions of policies and claims enriched with economic, health, geographic, and demographic signals \u2013 integrating cleanly with existing workflows to make complex risk clear, usable, and actionable.
- •Our customers include carriers, brokers, consultants, and specialized insurance organizations across the industry.
- •We are backed by $56M in Series C funding and scaling fast \u2013 and it's an exciting time to join the team! ", "key_responsibilities": " Leverage the best of modern deep learning & large language models with traditional data science techniques to create powerful hybrid models with real uplift.
- •Brainstorm, prototype, prove, deploy, and realize the value of your work in market quickly.
- •Solve world-class problems with big data, federated learning, unstructured data challenges, and timeseries and sequence modelling.
- •Tell stories with your data and inspire trust in customers, stakeholders, and prospects by turning murky math into a powerful message that drives the bottom line. ", "requirements": " Bachelor's degree in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 5+ years of professional data science experience building predictive models OR Master\u2019s or Ph.D in Computer Science, Data Science, Biostatistics, Mathematics, or similar related field AND 3-5 years of professional data science experience building predictive models.
- •Advanced proficiency with deep learning frameworks and the core Python data science ecosystem, and a deep understanding of modern AI architectures (e.g., Transformers, Neural Networks, LLMs) and related ML fields.
- •Strong technical communication and collaboration skills, particularly communicating with nontechnical stakeholders and working collaboratively with engineering/product teams to meet project goals and timelines.
- •MLOps and hands-on experience taking models from notebook to production \u2014 Experiment tracking, packaging, containerization (Docker), model serving and APIs, CI/CD, and pipeline orchestration.
- •Monitoring models in production \u2013 tracking data and concept drift and performance degradation, with alerting.
- •Strong peer leadership and ability to mentor junior DS on best practices and problem solving.
- •Experience setting and improving team standards. "}
Benefits & perks
Stock options, Unlimited vacation days, Flexible schedule, Medical insurance, Dental insurance, Vision insurance, 401k, Paid paternal leave
Tech stack
PythonTensorFlowPyTorchscikit-learnKerasOpenAI APIAnthropic APIGemini APILangChainHugging FaceComputer VisionNLPLLMsMLflowKubeflowSageMakerVertex AIONNXJAXPandasNumPySparkAirflowdbtTableauPower BILookerSnowflakeDatabricksFivetran