Jerry.ai is looking to solve the problem of car ownership and maintenance by using artificial intelligence and machine learning to simplify and automate the process, and is seeking an Applied Data Scientist to ensure data is clean, accurate, and reliable to drive critical business decisions.
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 identify data quality issues
- 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
- Proactively identify and handle missing values, outliers, and inconsistencies
- 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
- 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 team environment and collaborate with engineers, product managers, and business analysts
- Excellent communication skills and ability to communicate complex technical concepts to non-technical stakeholders
- Ability to work in a fast-paced environment and adapt to changing priorities
- Strong problem-solving skills and ability to investigate and resolve data discrepancies
