Junior Applied Data Scientist

Junior Applied Data Scientist

Jerry.ai is seeking a detail-obsessed Applied Data Scientist to join our growing team. The ideal candidate is passionate about ensuring data is clean, accurate, and reliable. You will be a detective at heart, driven by curiosity to understand complex data systems, and find satisfaction in transforming messy datasets into pristine assets that drive critical business decisions. This role offers the opportunity to own the entire data journey, from raw application data to clean inputs, model building, and delivering tangible value in real-world applications. You will serve as a central point of contact, collaborating 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, including statistical analysis, experimentation, and building, validating, and iterating on machine learning models to 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 such as tracking bugs, ETL errors, and 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, believing 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 actively seek out data quality issues and are persistent in seeing investigations through to resolution.
• Curious & Adaptive: You are inherently curious, possess a strong desire to understand how things work, and are comfortable with ambiguity and 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
• Data Cleaning
• Data Transformation
• Python
• SQL
• Data Quality
• Feature Store
• Statistical Analysis
• Problem Solving