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Full-time·Jerry

Data Scientist

Remote (United States)$110,000 - $140,000 per year + equity17 skills

Skills & Stack

Python (Pandas, NumPy, Scikit-learn)SQL (Advanced Querying & Optimization)Machine Learning (Supervised/Unsupervised)Statistical Analysis & Hypothesis TestingA/B Testing & Experimentation DesignData Visualization (Matplotlib, Seaborn, Plotly)Big Data Technologies (Spark, Hadoop)Cloud Platforms (AWS SageMaker, GCP Vertex AI)Deep Learning (TensorFlow/PyTorch)Natural Language Processing (NLP)Time Series ForecastingFeature EngineeringML Model Deployment (Flask, FastAPI)Business Intelligence Tools (Tableau, Looker)Insurance Domain KnowledgeFintech AnalyticsAutomotive Data Patterns

About the Role

As a Data Scientist at Jerry, you develop ML models that transform automotive insurance pricing and personalized recommendations. You analyze terabyte-scale datasets of driver behavior, claims history, and market trends to build predictive algorithms that power our AI assistant. This role offers hands-on experience with production-grade models impacting 500K+ monthly decisions - from risk assessment to customer lifetime value prediction. Collaborate with actuaries and engineers to deploy solutions that make car ownership smarter and more affordable for millions.

About Jerry

Jerry is an AI-powered insurtech leader revolutionizing car ownership with personalized insurance solutions. Our machine learning platform analyzes billions of data points to optimize insurance matching for 2M+ users. Combining fintech innovation with automotive expertise, weve created the first AI assistant that saves drivers money on insurance, financing, and maintenance. Backed by top VCs, Jerrys team of 500+ blends data science, insurance acumen, and consumer tech to simplify car ownership through data-driven decisions.

What You'll Do

10 items
  • 1Develop and optimize ML models for insurance risk assessment
  • 2Design A/B tests to measure impact of pricing algorithm changes
  • 3Build ETL pipelines for terabyte-scale automotive datasets
  • 4Create NLP models for customer interaction analysis
  • 5Implement time series forecasts for claims prediction
  • 6Collaborate with actuaries on regulatory-compliant models
  • 7Automate feature engineering for driver behavior data
  • 8Deploy models to production using AWS SageMaker
  • 9Analyze financial impact of model improvements
  • 10Research emerging techniques in insurtech ML applications

What We're Looking For

  • Bachelors/Masters in Data Science, Statistics, or related field
  • 2+ years experience applying ML in production environments
  • Expertise in Python data stack (Pandas, Scikit-learn, PySpark)
  • Advanced SQL skills (window functions, query optimization)
  • Experience with cloud ML platforms (AWS/GCP)
  • Knowledge of insurance/fintech domains (preferred)
  • Strong statistical foundation (Bayesian methods, regression)
  • Portfolio demonstrating end-to-end ML projects
  • Ability to explain complex models to business stakeholders
  • Passion for consumer fintech/automotive innovation
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