Associate Dir, Full Stack Data Scientist

Bayer•Cambridge, MA

6d•$131,600 - $197,400•Onsite

About The Position

The purpose of the Associate Director is to lead and deliver cross-functional Data Science capabilities enablement as a Full Stack Data Scientist in support of R&D Data Science needs for Bayer’s Pharmaceutical division. You will coordinate the activities that are needed and be hands- on in delivery of analytics stacks for R&D as part of the DSAI-DDRC team. The technology stack includes platforms, applications, integration tools, and analytics tools supporting processes within R&D. Additionally, you will coordinate the work conducted by external analytics developers and process capability stack operations, providing expert guidance to product team members to strategize, deliver, and execute on enablement tasks. This includes managing issue analysis, proper triage and issue assignments, and planning/communication of timelines and deployments in support of R&D DSAI. The primary location for this role can be either Cambridge, MA or Whippany, NJ. Remote work arrangements will not be accommodated for this role.

Requirements

Minimum of a Master’s Degree in Statistics, Mathematics, Informatics, Computer Sciences, ML Ops, Computer Engineering, or similar education
Proficiency in frontend technologies: such as React, Angular, or Vue.js, and AI enablement solutions such as Cursor
Strong experience with backend frameworks: like Node.js, Python (Flask, FastAPI, Django), or Java
Solid understanding of RESTful APIs, GraphQL, and WebSockets
Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
Familiarity with CI/CD pipelines, Git, and agile development practices
Knowledge of database systems: such as SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Redis)
Ability to work in a collaborative, interdisciplinary team environment
Experienced in GxP/CSV & IT project and/or business process design
Extensive experience in Data Science capability assessment and analysis
Demonstrated ability to address and resolve conflicts; proven collaboration skills
Pharma and life sciences domain experience
Applicable security and compliance experience
Exposure to machine learning workflows or experience integrating ML models into applications
Experience with data visualization libraries (D3.js, Plotly, etc.)
Understanding of MLOps or model deployment practices
Background in scientific computing, data engineering, or experimental software development
Demonstrated ability to lead through influence working in a cross functional team, building relationships with engineering teams and business stakeholders
Passion for digital transformation, change in general and play to win mentality

Nice To Haves

Project management experience is preferred

Responsibilities

Accountable to ensure the entire DS capabilities stack for the assigned process, and tasks are effective, efficient and meeting business operational needs
Hands on development of capabilities as required by the initiatives, mission leads, and product owners and other DSAI accountable parties
Identify business technology developments in the industry early on and actively promote them within the organization
Responsible for providing conceptual guidance to team members in appropriately designing certain capabilities as required to support the DSAI Analytics strategy
Ensure assigned business process area technology needs are met by interfacing and collaborating with the R&D functions; preparing and supporting delivery of DS capabilities and roadmaps in close collaboration with Head of DDRC and DSAI sub-clusters
Accountable to ensure process area capability issues are assessed upstream and downstream, communicated, coordinated and resolved promptly
Design, develop, and maintain full stack applications to support R&D initiatives
Collaborate with data scientists, ML engineers, and domain experts to translate research prototypes into production-ready tools
Build intuitive user interfaces and robust backend systems for data visualization, model interaction, and experimentation
Develop APIs and microservices to integrate with internal platforms and external data sources
Optimize performance, scalability, and reliability of R&D tools and applications
Participate in architectural discussions and contribute to technical strategy for R&D software infrastructure
Rapidly prototype new ideas and iterate based on feedback from researchers and stakeholders