Senior Data Scientist

Job Description: Develop large-sized machine learning models to surface critical business insights. Deploy large-sized machine learning models in production, collaborating with engineering teams and integrating into processes throughout MongoDB using AWS products, Python, and SQL. Supervise model maintenance for models deployed in production and support escalations cross-functionally across the data science product portfolio by handling communications with multiple affected teams and identifying sources of errors in the code. Does thorough and insightful peer code reviews to ensure quality and security of implementation from other data scientists. Collaborate with data engineering and data architecture teams to design and evaluate new data sets. Work with partner machine learning engineering teams to scope and evaluate new tools to improve the productivity of the Data Science Team. Work with leadership of Data Science Team and stakeholder teams on planning future initiatives. Handle maintenance and improvements of internal experimentation platform as a core code contributor; collaborates on feature design with Analytics and Engineering. Must appear in office 2 days per week; WFH permissible 3 days per week.

Requirements: Master’s degree or foreign degree equivalent in Statistics, Data Science, Mathematics, or related field and three (3) years of experience in Data Science (industry or research) or in the job offered or related role.

Experience and/or education must include:   

1. Machine Learning and statistical models, such as propensity modeling using classification models, causal inference, anomaly, changepoint and seasonality detection;

2. Applying SQL and MongoDB query language to query data from internal data warehouses

3. Unit, Integration, End-to-End testing and setting up alerting for deploying models in production using devops tools such as git, drone, PagerDuty, Splunk, Makefile and Python libraries such as pytest or unittest;

4. Deploying and maintenance of 3+ product propensity models using causal inference and uplift modeling in Python;

5. Using anomaly, changepoint and seasonality detection using Python libraries in 3+ projects;

6. Designing and running 3+ online experiments to test machine learning models in collaboration with business stakeholders; and

7. Applying distributed computing tools such as Kubernetes and Ray to deploy machine learning models in production.

JOB SITE: 1633 Broadway 38th floor, New York, NY 10019; Must appear in office 2 days per week; WFH permissible 3 days per week.

CONTACT: Please email resume to immigration@mongodb.com and reference Job ID#8157467