Data Scientist - Production Engineering

Role Description

We are looking to add a Data Scientist – Production Engineering to our data science team. This role focuses on operationalizing, optimizing, and scaling data science models and systems that are already in production or transitioning into production. Our data science work extends beyond traditional machine learning and includes:

• Statistical models
• Optimization logic
• Heuristics
• Rules-based systems
• ML and LLM models

This role is designed to strengthen the implementation and performance side of our data science stack while working closely with data scientists, engineering, and product teams. This role requires someone who can ramp up quickly, work independently, and contribute meaningfully without extensive onboarding.

Key Responsibilities

• Optimize existing data science models and systems for performance, scalability, and reliability
• Translate research-grade or prototype data science code into production-ready implementations
• Work with large datasets and improve efficiency related to memory usage, runtime, and compute cost
• Contribute to and maintain production data pipelines and workflows
• Collaborate closely with other data scientists to preserve model intent, correctness, and assumptions while improving implementation quality
• Debug and resolve issues in production or near-production data science workflows
• Improve robustness, monitoring, and maintainability of deployed models and pipelines
• Support iterative model improvements and system evolution as business needs change

Qualifications

• Bachelor’s degree or higher in Data Science, Computer Science, Statistics, Mathematics, or a related quantitative field
• 3+ years of experience working with real-world, industry, or production data in a data science, applied ML, or analytics role
• Demonstrated experience contributing to production data science or analytics systems
• Strong programming skills in Python and experience writing maintainable, production-quality code
• Experience working with large datasets and performance-sensitive workflows
• Prior experience with data pipelines and orchestration frameworks (e.g., Dagster, Airflow, etc.)
• Cloud platform expertise, particularly AWS services (Glue, Athena, ECS, S3 Tables, etc.) for scalable data processing and model deployments
• Hands-on experience with modern data warehouse solutions (Snowflake, BigQuery, etc.) including query optimization, clustering strategies, and cost management
• Experience with big data technologies and distributed computing frameworks for handling enterprise-scale event datasets
• Solid understanding of data science fundamentals, including statistics and modeling concepts
• Ability to work independently and ramp up quickly in an existing codebase and system
• Experience working in small, fast-moving teams where ownership and autonomy are expected

Benefits

• $140,000.00 - $175,000.00 base salary annually
• Equity and bonus
• Robust benefit plan (medical/dental/vision/life)
• 401k match
• Flexible time off and paid company holidays
• Annual company conference
• Childcare and continued education yearly reimbursements
• Healthy work/life balance
• Strong dedication to DE&I efforts
• Respectful and open culture