Senior Data Scientist

Summary

Join MongoDB's Platform Data Science team as a Senior Data Scientist for Engineering Systems and play a critical role in integrating machine learning algorithms into various engineering systems. Partner with engineering teams to deliver production-ready solutions, identify gaps in product coverage, and utilize novel datasets. Collaborate cross-functionally, contribute to code reviews and mentoring, and communicate technical concepts effectively. This role offers the flexibility of being based in New York City or remotely within the United States. You will help increase the velocity of data science model adoption across the business. MongoDB offers a supportive and enriching culture with various benefits.

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. Our codebase is primarily in Python
• 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.)

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

Benefits

• 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
• Equity
• Participation in the employee stock purchase program