Our client is seeking a Senior Data Scientist I with a strong actuarial background to join their Insurance Analytics team. This role is ideal for an actuarial professional who enjoys applying statistical modeling and data science to real-world insurance problems beyond traditional rate-making.
The Senior Data Scientist will develop predictive risk models and analytical attributes that help insurers improve underwriting, risk segmentation, pricing, and decision-making . The ideal candidate will have hands-on experience with actuarial modeling, GLMs, statistical analysis, and Python, along with an understanding of how predictive models are incorporated into insurance workflows.
APay: 130k - 150k
Key Responsibiliti
- esDevelop predictive risk models and attributes used in underwriting, segmentation, and insurance decisionin
- g.Apply actuarial principles and statistical modeling techniques to evaluate risk and improve model performanc
- e.Build and support models such as GLMs and tree-based metho ds for insurance application
- s.Design models that can be integrated into carrier underwriting processes and downstream pricing framework
- s.Analyze and manage large, complex datasets from multiple source
- s.Prepare, clean, transform, and validate data for statistical modeling and analysi
- s.Apply data quality, testing, and model performance monitoring best practice
- s.Translate complex analytical findings into clear, actionable insights for Product, Business, and other stakeholder
- s.Partner with Product and Vertical teams to solve insurance-specific problems related to risk evaluation and segmentatio
- n.Support model development, maintenance, enhancement, and production implementatio
- n.Contribute independently to project workstreams while collaborating on larger, complex initiative
- s.Communicate project progress, analytical insights, and outcomes effectivel
- y.Stay current with data science, actuarial, statistical, and insurance industry trends and technologies
s.Required Qualificatio
- nsBachelor's degree in a relevant field with 4+ years of relevant experien ce,
- ORMaster's degree in a relevant field with 2+ years of relevant experien ce,
- ORPhD in a relevant fiel
- d.Strong actuarial foundation with experience applying actuarial concepts to insurance risk, underwriting, or segmentati o
- n.Strong proficiency in Pyth on for statistical modeling and data analysi
- s.Experience developing or supporting risk segmentation mode ls, including GLMs, within an insurance environmen
- t.Experience with insurance data, risk modeling, or underwriting-related problem
- s.Experience translating actuarial/statistical models into production-ready analytical solutio n
- s.Strong understanding of statistical and mathematical modeling, including model assumptions, diagnostics, interpretability, linear/nonlinear models, and machine learning technique
- s.Ability to independently prepare, clean, transform, and analyze large, complex dataset
- s.Strong analytical, problem-solving, and communication skill
- s.Ability to independently own project components, manage priorities, and meet deadline
s.Preferred Qualificatio
- nsProgress toward ASA or equivalent actuarial credentia ls strongly preferre
- d.Experience with R, SQL, and/or E C
- L.Experience working with Department of Insurance filin g
- s.Experience with insurance pricing and underwriting workflow
- s.Familiarity with regulatory requirements and model governanc
- e.Experience with additional machine learning techniques and predictive modelin
- g.Ability to learn new technologies quickly and share knowledge across cross-functional team