Senior Data Scientist - Engineering Systems

Overview

As a Senior Data Scientist within the Engineering Systems team at MongoDB, you will collaborate closely with skilled engineers from teams such as Server Query, Atlas Clusters, and Release Quality. Your role will focus on tackling complex challenges including resource scaling throughout the Atlas infrastructure, ensuring safe feature rollouts to MongoDB clusters, automating incident responses, and optimizing query engine performance. You will contribute to researching, prototyping, and deploying machine learning capabilities embedded deeply in MongoDB's core server, query engine, and its cloud-based service, Atlas.

The role operates within a hybrid work model primarily in Dublin or Cork offices.

Key Responsibilities

• Collaborate with engineers across different teams (Server Query, Atlas Clusters, Release Quality) to integrate algorithmic optimizations and statistical rigor into systems handling resource scaling, release assurance, and monitoring within the server fleet and query engine.
• Develop and deliver well-tested, production-quality statistical and machine learning algorithms that produce clear business impact rather than just theoretical merit.
• Manage the full product feedback cycle by instrumenting models with appropriate metrics, partnering with analytics teams to create dashboards, and using user feedback and performance data to refine and enhance models.
• Provide constructive and considerate code reviews, contribute significantly to internal tools, libraries, and workflows to boost team productivity and code quality.

Success Milestones

• By three months: Familiarize with workflows, gain basic product understanding, and contribute small to medium improvements.
• By six months: Research, prototype, and implement at least one significant feature demonstrating measurable business benefit.
• By twelve months: Establish a consistent track record of impactful machine learning solutions enhancing fleet stability, efficiency, or automation, deepen collaborations with multiple engineering teams, and serve as a resource on statistical and engineering best practices.

Skills and Qualifications

• Over five years of applied experience in developing machine learning models working directly with technical stakeholders.
• Proven ability to independently manage the entire machine learning lifecycle, including prototyping, simulation, tuning, and deployment iteration both with and without dedicated engineering support.
• Expertise in designing scalable, readable, object-oriented Python codebases and collaborative skills contributing to ML system architecture design.
• Adeptness in both writing and reviewing code of any origin, including AI-generated code, to maintain high-quality software standards.
• Commitment to fostering a supportive team culture that encourages psychological safety and open communication, adapting to personal styles to promote a positive environment.
• Effective communication skills to explain complex ML concepts and translate model performance into tangible business impacts for non-technical audiences.
• Master's degree or equivalent in computational or quantitative fields such as computer science, applied mathematics, statistics, physics, or operations research.

About MongoDB

MongoDB empowers customers to lead innovation by redefining data platforms for the AI age. Its unified data platform is widely recognized for modernizing workloads and enabling AI-centric applications globally across cloud providers including AWS, Google Cloud, and Azure. With a widespread customer base including 75% of Fortune 100 firms, MongoDB is a pioneer in software advancement.

The company prioritizes leadership values that guide decision-making, collaborative culture, and success. It supports employees with affinity groups, fertility help, and generous parental leave policies to promote professional and personal growth. MongoDB is committed to accessibility in recruitment and to equal opportunities for all applicants.

Additional Information

MongoDB is dedicated to accommodating applicants with disabilities throughout the hiring process upon request.