Filtr uses AI to scan 1000+ jobs and finds postings that perfectly matches your resume

MongoDB is looking to integrate predictive solutions into systems across the company to drive broad impact, increase adoption of data science models, and improve business outcomes and operational efficiencies through AI/ML model development and statistical thought partnership.

Requirements

• 8+ years of hands-on data science and machine learning model development
• Embraces an object-oriented approach to designing scalable and readable Python codebase, and has experience working with engineers on architectural design of machine learning systems
• Expertise and track record of 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
• Ability to translate efficacy measurements of data science models and products into tangible business impact metrics

Responsibilities

• Represent the MongoDB Data Science team to business stakeholders across different verticals, navigating the translation layer between business unit requirements and cutting-edge technical solutions
• Proactively propose new solutions based on business priorities derived from close collaboration with product managers and other engineers
• Own end-to-end implementation of data science projects (feasibility analysis, data preparation, feature engineering and model evaluation, as well as deployment and maintenance)
• Provide thought leadership to the broader organization on the best way of using machine learning technologies, frameworks and approaches to solve different problems
• Evangelize appropriate tech and engineering best practices
• Define and improve business & product metrics to optimize the quality and cost of AI usage
• Maintain a high standard of operational excellence across the team by streamlining workflows and acting as a core code contributor to internal packages, tooling, and team processes

Other

• Proven track record of coordinating and collaborating effectively with stakeholders and end-users of data science products to ensure the delivery of fit-for-purpose solutions
• Effective at communicating technical concepts to non-technical audiences, including business leadership
• Committed to contributing to a collaborative, enjoyable, and psychologically safe work environment
• PhD or Masters degree in a quantitative/computational discipline (computer science, applied mathematics, statistics, physics, operations research, etc.)