Senior Data Scientist

Zebra Strategies

. Collaborate with Product Managers, Engineers, and Analysts to scope and deliver Data Science opportunities .

Posted 10/28/2026full-timeRemote • United StatesSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and deploying machine learning models, with a strong foundation in Python and data science methodologies. Capable of collaborating with cross-functional teams to drive data-driven solutions and continuous improvement in data science practices.

Highest-signal resume keywords

Machine Learning Model DevelopmentPython ProficiencyData Science Lifecycle ManagementStatistical Analysis and Experimental DesignMentoring and Collaboration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine LearningStatistical ModelingRegression AnalysisClassificationClusteringCausal MeasurementReinforcement LearningCI/CDData WranglingProduction Code Development

Soft Skills

Strong CommunicationCollaborationContinuous Improvement OrientationMentoring

Tools & Technologies

PythonSklearnPandasPolars

Industry Keywords

B2C ContextAuction SystemsBidding SystemsReal-Time Allocation SystemsIncrementality TestingGeo TestsMMM

Tech Stack

Tools & technologies

PandasPythonScikit-Learn

About the role

Key responsibilities & impact

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

What you’ll need

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

Comp & perks

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