Senior Data Scientist

MongoDB’s mission is to empower innovators to create, transform, and disrupt industries by unleashing the power of software and data. We enable organizations of all sizes to easily build, scale, and run modern applications by helping them modernize legacy workloads, embrace innovation, and unleash AI. Our industry-leading developer data platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available in more than 115 regions across AWS, Google Cloud, and Microsoft Azure. Atlas allows customers to build anywhere—on the edge, on premises, or across cloud providers. With offices worldwide and over 175,000 developers joining MongoDB every month, it’s no wonder that leading organizations, like Samsung and Toyota, trust MongoDB to build next-generation, AI-powered applications.

The Senior Data Scientist will play a critical role in driving impact at MongoDB through researching, prototyping and integrating predictive solutions into systems across the company.  As a member of the Business Data Science team, the Senior Data Scientist will partner closely with other teams including Go To Market, Sales, Product, and IT 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 will be based out of our New York City office.

This role will have key internally-facing leadership responsibilities, including:

• Developing, deploying, and maintaining Machine Learning models to equip internal teams with actionable tools to drive enterprise growth
• Working with many stakeholders across different verticals, navigating the translation layer between business unit requirements, key business metrics, and cutting-edge technical solutions
• Delivering data-driven insights to guide strategic decisions and optimize outcomes
• Leveraging and continuing to grow the Data Science team’s capabilities through technical and business-savvy mentorship

(Additional) Responsibilities

• Act as a conduit between MongoDB Data Science and business stakeholders across Product, Engineering, and GTM teams
• Own end-to-end implementation of data science projects (feasibility analysis, data preparation, feature engineering and model evaluation) in collaboration with data analysts, other data scientists, data engineers, software engineers, product managers, and business stakeholders
• Communicate, coordinate, and collaborate effectively with end-users of data science products and respond to stakeholder needs
• Provide thought leadership to the broader organization on the best way of using machine learning technologies, frameworks and approaches to solve different problems
• Collaborate closely with product managers and other engineers to understand business priorities, propose new solutions
• Identify data gaps, working with engineering to collect and effectively use novel data sets
• Act as a core code contributor to internal platform tools

Skills & Attributes

• 5+ years of hands-on data science and machine learning model development
• Experience working alongside product and engineering teams to deliver measurable value to the customer with predictive solutions
• Familiarity and comfort working in a large scale environments with unstructured or semi-structured data using SQL and Python (MQL plus) 
• Clear understanding of the risks and trade-offs involved in choosing different models
• Demonstrated understanding of the entire data science development lifecycle, including experience delivering data science artifacts to production deployment environments 
• Ability to seek empirical evidence through proofs of concept, statistical validation and external research
• Ability to translate efficacy measurements of data science models and products into tangible business impact metrics
• Effective at communicating technical concepts to non-technical audiences, including business leadership
• 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.)

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys.