Senior Data Scientist, MongoDB
Engineering Systems
$126-248k
Developer data platform
Be an early applicant
Developer data platform
1001+ employees
Be an early applicant
$126-248k
1001+ employees
Company mission
To empower innovators to create, transform, and disrupt industries by unleashing the power of software and data.
Role
Who you are
- 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.)
What the job involves
- 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
- 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
Our take
MongoDB is an open-source, cross-platform, document-oriented database system. It stores data as JSON-like documents and is written in C++, Go, JavaScript and Python.
Essentially, the company develops tools and blueprints to help businesses and organisations modernise their legacy applications, migrating them to the MongoDB database and the MongoDB Atlas cloud database. With this initiative, MongoDB is particularly taking aim at Oracle customers with ageing applications running on the Oracle relational database system.
Since its release, MongoDB has become one of the most popularly used NoSQL database systems due to its ease of use and efficiency. It is also the fastest-growing database ecosystem, and boasts hundreds of millions of downloads. Recently, the company announced a partnership with Patronus AI, an automated evaluation and security platform, through which it will bring automated LLM evaluation and testing capabilities to enterprise customers.
Freddie
Company Specialist at Welcome to the Jungle
Insights
13% employee growth in 12 months
Company
Funding (last 2 of 8 rounds)
Jan 2015
$80m
SERIES G
Oct 2013
$150m
SERIES F
Total funding: $311.1m
Company benefits
- Rich health insurance coverage
- Virtual & on-site fitness classes
- Health screenings & telemedicine
- Access to transgender-inclusive health insurance coverage
- Global and internal mobility opportunities
- Equity & Employee Stock Purchase Program
- Pension & retirement programs
- Income Protection
- Flexible PTO is offered to every US employee & competitive time off policies for non-US employees
- Employee Assistance Program
- Mental health counseling
- Free meditation app access
- Fertility & adoption financial assistance
- Parental counseling for new parents
- 20 weeks of fully paid gender neutral parental leave & flexible work arrangements
- 4 weeks of emergency care leave
Company HQ
Theater District, New York, NY
Leadership
Dwight Merriman
(Co-Founder)Previously CTO and Co-founder at DoubleClick for 10 years, and Chairman at AlleyCorp for 15 years.
Salary benchmarks
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