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Company

Original Job Post

Everest · 3 days ago

Principal Data Scientist

Walnut Creek, CA

Full-time

Hybrid

Senior Level

$170K/yr - $200K/yr

5+ years exp

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Insurance

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Responsibilities

Work independently with business stakeholders to translate business problems into tractable data science projects.

Lead large data science initiatives that involve multiple data scientists and data engineers.

Mentor and coach junior data scientists.

Develop and structure projects in a clear, organized, and robust manner to ensure high-quality products.

Be comfortable working with ambiguity, anticipating roadblocks, and scrutinizing assumptions.

Be delivery focused: Exhibit creative problem-solving skills, focus on outcomes, adhere to timelines, and deliver results.

Work with stakeholders to develop implementation plans for analytical projects to drive adoption and business use.

Develop and implement techniques for model monitoring, maintenance, and business evaluation.

Promote a data-driven culture throughout the organization. Engage in conversation with the business around “the art of the possible using data science.”

Qualification

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End-to-End Model BuildExploratory Data AnalysisModel DeploymentReal-Time ModelsMachine Learning AlgorithmsStatistical ModelingR ProgrammingPython ProgrammingSQL ProficiencyResearch DesignHypothesis TestingData AnalysisStrategic Decision MakingActuarial CollaborationTechnical PresentationProblem-SolvingCollaborationCommunication

Required

Passion for driving change and achieving goals.

Experience with end-to-end model build and delivery, from business understanding to exploratory data analysis to model building and deployment.

Familiarity with productionalizing real-time, near-real time, and batch models.

5+ years applied experience as a data scientist in a related field.

Direct experience within the Insurance Industry desired.

Experience working with actuaries on data science projects is a plus.

Proven record of delivery of data-driven insights and advanced analytic models to inform strategic decision making.

BS (advanced degree MS/PhD preferred) in quantitative discipline such as Statistics, Engineering, Math, Physics, etc.

Extensive experience with machine learning algorithms such as random forest, gradient boosting, deep learning, and support vector machines as well as techniques like natural language processing, bootstrapping, cross-validation, and stratified sampling.

Experience and knowledge of statistical modeling including OLS, generalized linear regression, time series analysis, survival models, and structural equation modeling.

Strong proficiency with R and/or Python.

Proficiency with SQL.

Experience with research design, hypothesis testing, design of experiments, analyzing data, and developing actionable recommendations for business units.

Ability to collaborate and communicate with a variety of audiences and partners.

Experience presenting technical materials to non-technical audiences.