Lead ML / Data Scientist in Gurugram, India

ProcDNA is a global consulting firm. We fuse design thinking with cutting-edge tech to create game-changing Commercial Analytics and Technology solutions for our clients. Instead, you'll be out in the open water, shaping the future with brilliant minds. We are looking for a Lead Data Scientist who can own data science engagements end to end, from shaping the problem with the client to delivering and operationalizing ML solutions. You will lead a team of data scientists, guide technical decisions, and help grow ProcDNA's data science practice through client relationships and new capabilities.

Work with clients to translate business questions into well-scoped data science problems, and define the approach, data requirements and success measures.

Design and oversee ML solutions across the pharma commercial lifecycle, and choose methods that fit the data and the decision they support.

Quality-check the team's work and guide models to production through cross-team collaboration.

Lead project delivery across timelines, scope and team allocation, often across parallel engagements.

Mentor and manage a team of data scientists, and keep yourself and the team current with advancements in the field for collective growth.

Contribute to business development and internal capability building through proposals, POCs and reusable offerings, and help the practice grow

5.5+ years of hands-on experience in data science and ML, with at least 2 years leading projects or teams in a pharma consulting or client-facing setting.

• A Bachelor's or Master's degree in engineering, statistics, mathematics or a relevant quantitative field.
• Experience with life sciences data, such as claims (Komodo, IQVIA, Symphony), specialty pharmacy, CRM, DDD, Lab and other HCP, account or patient-level data.
• Strong depth in Statistics, supervised and unsupervised ML, Deep learning and GenAI concepts, along with experience in deploying models to production.
• Strong Python and SQL, with experience on distributed or cloud platforms such as Databricks, PySpark and AWS/Azure.
• A track record of owning client communication and explaining results to non-technical stakeholders.
• Experience in guiding and managing a team of data scientists.