Jerry.ai is looking to solve the problem of car ownership and maintenance by simplifying and automating the process using artificial intelligence and machine learning, with the goal of becoming a $10B business in the next few years
Requirements
- Strong proficiency in Python (Pandas/NumPy) and SQL for complex querying and data manipulation
- Hands-on experience with data cleaning techniques and data validation frameworks
- Familiarity with data visualization tools to help identify and communicate data issues
- Bachelor’s degree (PhD preferred) in a quantitative field (Statistics, Physics, Mathematics, etc.)
- Experience with machine learning models and statistical analysis
- Ability to work with complex data systems and transform messy datasets into pristine assets
- Knowledge of data engineering and data architecture
Responsibilities
- 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
- Own the data foundation by preparing, cleaning and transforming raw, complex data into high-quality features for modeling
- Investigate data discrepancies (tracking bugs, ETL errors, definitional issues) and design automated frameworks to ensure data accuracy
- Act as a strategic liaison, collaborating with data Engineering and product teams to drive the data strategy and definition of our centralized feature store
- Create and maintain clear, authoritative documentation for data sources, cleaning processes, and variable definitions
- Proactively identify and handle missing values, outliers, and inconsistencies in data
- Build models and deliver tangible value in real-world applications
Other
- Bachelor’s degree (PhD preferred) in a quantitative field (Statistics, Physics, Mathematics, etc.)
- Ability to work in a fast-paced environment and collaborate with cross-functional teams
- Excellent communication and problem-solving skills
- Ability to work with ambiguity and adapt to changing priorities
- Strong attention to detail and low tolerance for errors
