Director I, Data Science
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The Product Design and Modeling team within Global Retail Markets is looking for an individual contributor for its Complex Components group. The Complex Components group develops sophisticated models that are used as either inputs or complements to our core pricing programs. This individual contributor role will be a part of the Complex Components leadership team, reporting directly to the head of Complex Components, and be tasked with constructing and architecting modeling tools and pipelines to massively enhance the productivity and effectiveness of the entire Complex Components group. The ideal candidate is proactive, highly technical, and most importantly driven by a desire to advance our organization by orders of magnitude and push the boundaries of what we think is possible.
- Partner with Complex Components teams to build and design model deployment architecture
- Manage, design and build predictive modeling tools for use across Complex Components
- Participate in development of Complex Components strategic priorities
- Proactively identify novel ways to add value for GRM pricing and underwriting through predictive modeling
- Coach and mentor junior analysts throughout the department
- Build community across the team, helping create an environment where people love to work
Competencies typically acquired through a Ph.D. degree (in Statistics, Mathematics, Economics, Actuarial Science or other scientific field of study) and a minimum of 3 years of relevant experience, a Master`s degree (scientific field of study) and a minimum of 6 years of relevant experience or may be acquired through a Bachelor`s degree (scientific field of study) and a minimum of 8 years of relevant experience.
- Highly competent in Python and an interest in and openness to learning pipeline and model deployment tools
- Ability to think critically and challenge existing approaches
- Strong ability to focus on and execute projects
- Ability to quickly gain a foundational understanding on a variety of domains
- Deep knowledge of predictive modeling techniques