Associate Applied Data Scientist

Why Jerry.ai

Join a profitable pre-IPO startup with capital, traction, and runway ($240M funded | 60X revenue growth in 5 years | $2T market size). Work closely with brilliant leaders and teammates from companies like Amazon, Better, LinkedIn, McKinsey, BCG, Bain. Disrupt a massive market and take us to a $10B business in the next few years. Our growth is driven by forward-thinking technology: Jerry.ai is getting mentioned in many conversations about our use of GenAI, such as this Forbes article. Be immersed in a talent-dense environment and greatly accelerate your career growth. Impact millions of users experience with car maintenance and auto insurance.

About The Opportunity

We are looking for a detail-obsessed Applied Data Scientist to join our growing team. The ideal candidate is passionate about the foundational layer of all data analysis: ensuring our data is clean, accurate, and reliable. You are a detective at heart, driven by a deep curiosity to understand complex data systems, and someone who finds immense satisfaction in transforming messy, ambiguous datasets into pristine assets that drive critical business decisions.

This role is perfect for a scientist who wants to own the entire journey: from taking raw application data to generating clean inputs, to building models and delivering tangible value in real-world applications. You will be a central point of contact, communicating with engineers, product managers, and business analysts to ensure data integrity from collection to analysis.

How you will make an impact

• Model Ownership: Participate in the full modeling lifecycle, from statistical analysis and experimentation to building, validating, and iterating on machine learning models that address critical business challenges.
• Data Quality: Own the data foundation by preparing, cleaning and transforming raw, complex data into high-quality features for modeling. Proactively identify and handle missing values, outliers, and inconsistencies.
• Problem Investigation: Investigate data discrepancies (tracking bugs, ETL errors, definitional issues) and design automated frameworks to ensure data accuracy.
• Cross-Functional Collaboration: Act as a strategic liaison, collaborating with data Engineering and product teams to drive the data strategy and definition of our centralized feature store, ensuring it becomes the 'single source of truth' for all ML models.
• Documentation: Create and maintain clear, authoritative documentation for data sources, cleaning processes, and variable definitions.

Who You Are

• Obsessed with Details: You have an exceptional eye for detail and a low tolerance for errors. You believe that accuracy and precision are non-negotiable.
• A Strategic Thinker: You can see the bigger picture and are passionate about building robust systems and processes that will stand the test of time.
• Proactive & Persistent: You don't wait for problems to find you. You actively seek out data quality issues and are persistent in seeing an investigation through to its resolution.
• Curious & Adaptive: You are inherently curious and possess a strong desire to understand how things work. You're comfortable with ambiguity and skilled at breaking down complex problems.

Requirements

• Education: Bachelor’s degree (PhD preferred) in a quantitative field (Statistics, Physics, Mathematics, etc.).
• Programming: Strong proficiency in Python (Pandas/NumPy) and SQL for complex querying and data manipulation.
• Data Quality: Hands-on experience with data cleaning techniques and data validation frameworks.
• Tooling: Familiarity with data visualization tools to help identify and communicate data issues.

Key skills/competency

• Data Science
• Machine Learning
• Python
• SQL
• Data Cleaning
• Data Validation
• Statistical Analysis
• Feature Engineering
• Problem Solving
• Collaboration