Senior Data Scientist, Engineering Systems

About the position

The Senior Data Scientist for Engineering Systems will play a critical role in driving impact at MongoDB through researching, prototyping and integrating machine learning algorithms into systems across the broader engineering organization. As a member of the Platform Data Science team, the Senior Data Scientist will partner closely with engineering teams such as Core Database Engine, Release Quality, Database Performance Testing, and Developer Productivity teams to further our team mission: 'Delivering fit-for-purpose, practical, and production-ready solutions to drive business outcomes and operational efficiencies through AI/ML model development and statistical thought partnership'. We are growing adoption of data science models across the business, and you will help us increase this velocity substantially. This role can be based out of our New York City office or remotely in the United States.

Responsibilities

• Delivering production ready, thoroughly tested statistical and machine learning algorithms with well-identified limitations
• Collaborating cross-functionally with engineers from various teams to iterate on ML service architecture within a production environment
• Identifying gaps in product coverage and working with Engineering, Data Architecture and Data Engineering teams to collect, transform and use novel data sets effectively
• Delivering thoughtful and kind code reviews to your fellow team members and mentoring more junior data scientists
• Collaborating with Engineering, Product Analytics and Product Management on identifying promising areas for applying machine learning algorithms
• Communicating, coordinating, and collaborating effectively with stakeholders and taking a proactive role in shaping new relationships with Engineering teams
• Acting as a core code contributor to internal packages, tooling and team processes

Requirements

• 5+ years of hands-on machine learning model development
• Embraces an object-oriented approach to designing scalable and readable Python codebase, and has experience working with engineers on architecture design of machine learning systems
• Expertise and track of record working autonomously across the entire data science development lifecycle, including prototyping, simulation, tuning and delivering data science artifacts to production deployment environments with and without dedicated engineering help
• Effective at communicating technical concepts to non-technical audiences; e.g. able to translate efficacy measurements of data science models and products into tangible business impact metrics
• Committed to contributing to a collaborative, enjoyable, and psychologically safe work environment
• Master's degree or equivalent experience in a quantitative/computational discipline (computer science, applied mathematics, statistics, physics, operations research, etc.)

Benefits

• Equity
• Participation in the employee stock purchase program
• Flexible paid time off
• 20 weeks fully-paid gender-neutral parental leave
• Fertility and adoption assistance
• 401(k) plan
• Mental health counseling
• Access to transgender-inclusive health insurance coverage
• Health benefits offerings