[NJ] Engagement Lead - Analytics

About ProcDNA

ProcDNA is a global rocket ship in life sciences consulting. We fuse design thinking with cutting-edge tech to create game-changing Commercial Analytics and Technology solutions for our clients. Were a passionate team of 450+ across 9 offices, all growing and learning together since our launch during the pandemic. Here, you wont be stuck in a cubicle - youll be out in the open water, shaping the future with brilliant minds. Ready to join our epic growth journey?

What we are looking for

ProcDNA is seeking a Data Scientist to join our team. The ideal candidate brings deep experience leading advanced analytics and machine learning work in the pharma industry and can translate complex business problems into clear analytical strategies. You are comfortable owning end-to-end delivery, leading client conversations, mentoring teams, and shaping internal product offerings that can be scaled across engagements.

What you will do

• Drive end-to-end data science projects, including problem framing, exploratory data analysis, feature development, and model development and validation, taking lead on approach decisions and tradeoffs.
• Build internal product offerings and reusable accelerators, such as packaged modeling workflows and internal ML and AI products.
• Set and enforce standards for rigor, documentation, and reproducibility across the workstream, ensuring outputs are audit-ready and client-ready
• Lead client discussions and presentations, translating technical results into clear business wins.
• Partner with data and engineering teams as needed to operationalize outputs, including repeatable pipelines, handoffs, and monitoring considerations

Must Have

• Master's degree or higher in a quantitative field with a strong academic record.
• 5-7 years of relevant experience in data science with a focus on advanced analytics and applied ML.
• Strong applied Statistical foundation for building and evaluating models
• Strong experience with ML and AI modeling concepts and practical application across multiple projects. Expertise in SQL and strong fluency with relational datasets.
• Extensive Python or R experience for analysis and modeling.
• Excellent communication skills, verbal and written, with strong client-facing presence.
• Strong problem-solving mindset, detail orientation, and ability to independently manage dynamic, multi stakeholder workstreams.