Senior Data Scientist
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Job Description
Senior Data Scientist building production machine-learning models for The Zebra’s online car and home insurance marketplace. Owning experimentation, deployment, and model impact analysis.
Responsibilities:
- Collaborate with Product Managers, Engineers, and Analysts to scope and deliver Data Science opportunities
- Own the Data Science lifecycle end to end, from wrangling warehouse data to building and deploying models, analyzing experiment results, and quantifying model impact
- Build machine learning models to personalize the product and connect users with suitable insurance policies
- Work with cross-functional stakeholders to understand business needs and develop ML-based solutions
- Analyze product data, design experiments, and drive collection and integration of new data sources
- Write clean, maintainable production code to operationalize models using software-engineering best practices
- Perform peer code reviews
- Mentor other data scientists
- Drive continuous improvement in the platform and data-science practices
Requirements:
- 5+ years experience in a technical data role
- 3+ years of hands-on experience building machine learning / statistical models
- Proven mathematical foundation
- Knowledge of regression, classification, clustering, and experimental design
- Solid foundation in software engineering
- Strong proficiency in core Python and the Python data ecosystem, including sklearn and pandas/polars
- Comfortable owning models in production, including CI/CD, testing, orchestration, monitoring, and retraining
- Strong ownership, communication, collaboration, and continuous-improvement orientation
- Experience mentoring junior data scientists is a plus
- Experience modeling customer/human behavior in a B2C context is advantageous
- Experience building ML for auction, bidding, or real-time allocation systems is advantageous
- Experience designing and interpreting causal measurement, including experiments, quasi-experimental methods, incrementality testing, geo tests, and MMM, is advantageous
- Experience with reinforcement learning in production, especially contextual bandits, is advantageous
- Experience building ML platforms is advantageous
- Must be legally authorized to work in the United States
- Position is not eligible for visa sponsorship or visa transfers
- Must be based in the United States, excluding California and Massachusetts
Benefits:
- Competitive Compensation & Stock Option Offering
- Health, Dental, Vision & Disability Coverages
- HSA offering + employer contribution
- 401k plan + employer match
- Unlimited PTO (paid time off) - with a three-week minimum we actually track
- Paid Parental Leave Program
- Wellness perk ($100/month)
- Pet Adoption Reimbursement ($300/year)
- Learning & Development Opportunities
- Employee Resource Groups
- Remote work option
- Option to join the Austin office or opt for a hybrid setup for employees around Austin
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