Lead Data Scientist
Weekday AI (company site, opens in a new tab)7+ yrsPuneOn-siteDirect career pageEst. 30–40 LPA
Posted 20h ago
Reach people at Weekday AI
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at Weekday AI you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Lead and deliver end-to-end advanced analytics and AI/ML projects for global pharmaceutical and life sciences clients, focusing on commercial and marketing business challenges.
- Translate complex pharmaceutical commercial data and analytics into actionable insights and scalable data-driven solutions, ensuring measurable business impact.
- Lead, mentor, and manage data science teams, uphold technical excellence, and maintain high-quality project delivery and client engagement.
Minimum Requirements
- 7+ years of professional experience in data science with leadership and client-facing roles.
- Advanced proficiency in Python and SQL for data analysis and machine learning.
- Hands-on experience in pharmaceutical commercial and marketing analytics using datasets like prescription, claims, and market intelligence data.
- Work Experience Required: 7+ years; Location: Pune, Maharashtra, India; Employment type: Full-time.
Ideal Candidate Profile
- Experienced in delivering pharmaceutical commercial and marketing analytics including Sales, Market, Brand, and Forecasting use cases.
- Technically strong in statistical modeling, forecasting, machine learning, cloud technologies, and data visualization (Power BI/Tableau).
- Skilled in client engagement, stakeholder management, and mentoring analytics teams within global pharmaceutical or life sciences environments.