Lead Data Scientist – Pharma Analytics

Location: Bengaluru

Experience: 8-11 Years

We are hiring a Lead Data Scientist – Pharma Analytics to lead client-facing analytics engagements and deliver advanced AI/ML solutions for global pharmaceutical organizations.

The ideal candidate will possess deep expertise in Pharma Commercial Analytics, Marketing Analytics, Machine Learning, Advanced Analytics, and Data Science delivery , with strong hands-on experience in Python, SQL, Cloud technologies , and pharma datasets. The role requires balancing technical excellence, stakeholder management, and team leadership while translating complex business problems into scalable analytics solutions.

Key Responsibilities:

Analytics & Solution Delivery

- Partner with business stakeholders and clients to understand business challenges and translate them into analytical solutions.
- Design and deliver scalable data science and advanced analytics solutions.
- Lead end-to-end analytics projects from problem definition through deployment and impact measurement.
- Develop predictive models, forecasting solutions, machine learning algorithms, and optimization frameworks.
- Drive insights generation through statistical modelling, machine learning, segmentation, forecasting, and performance analytics.
- Present actionable recommendations and storytelling-driven insights to senior client stakeholders.

Team Leadership

- Lead, mentor, and develop a team of Data Scientists and Analysts.
- Conduct technical solution reviews, code reviews, and mentoring sessions.
- Drive adoption of best practices across Data Science, AI/ML, Cloud, GenAI, and Analytics delivery.
- Ensure high-quality and timely project execution.

Client Engagement





- Collaborate closely with Pharma Commercial, Marketing, Brand, Sales, Market Access, and Strategy teams.
- Participate in solution design, capability building, proposal development, and client presentations.
- Build strong relationships with senior stakeholders and act as a trusted analytics advisor.

Required Skills (Must Have):

Core Technical Skills

- Advanced proficiency in Python
- Advanced proficiency in SQL
- Strong expertise in:
- Machine Learning
- Predictive Modeling
- Statistics
- Hypothesis Testing
- Feature Engineering
- Model Validation
- Forecasting
- Data Visualization:
- Power BI (Preferred)
- Tableau (Alternative)
- Cloud exposure in at least one: AWS, Azure, GCP

Skill Mix 1: Commercial Pharma Analytics:

Mandatory Pharma Analytics Experience

Hands-on experience in one or more of:

- Commercial Analytics
- Sales Analytics
- Market Analytics
- Brand Analytics
- Performance Analytics
- Forecasting Analytics

Pharma Data Sources Strong working knowledge of at least some of the following:
- IQVIA
- Symphony Health
- MMIT
- Truven
- HealthJump
- Prescription Data
- Claims Data
- Patient-Level Commercial Data

Preferred Use Cases
- Sales Force Effectiveness
- Territory Alignment
- Targeting & Segmentation
- Commercial Performance Measurement
- Incentive Compensation Analytics
- Launch Analytics
- Market Share Analytics





Skill Mix 2: Marketing Analytics & AI/ML: Mandatory Pharma Marketing Analytics Experience

Strong experience in commercial and marketing analytics within pharmaceutical or life sciences organizations.

Marketing Analytics Expertise

Hands-on experience in one or more of:

- Marketing Mix Modeling (MMM/MMX)
- Multi-Touch Attribution (MTA)
- Campaign Effectiveness
- Customer Segmentation
- Omnichannel Analytics
- Customer Journey Analytics
- Next Best Action (NBA)
- Forecasting Models

AI/ML Applications in Pharma

Experience in

- Predictive Analytics
- Machine Learning
- Time Series Forecasting
- Recommendation Engines
- NLP Applications
- Customer Analytics
- Physician Analytics
- GenAI Solutions
- LLM-based Applications

Positive to Have:

- Generative AI and Agentic AI applications
- NLP and LLM-based Analytics
- Time Series Forecasting
- MLOps
- Databricks
- Snowflake
- Healthcare/Pharma Consulting experience
- Experience working with global pharmaceutical clients
- Exposure to advanced cloud-based ML deployments

Leadership Competencies:

- Strong analytical and problem-solving mindset.
- Ability to independently drive client conversations.
- Proven stakeholder management skills.
- Experience mentoring and developing analytics teams.
- Ability to manage multiple projects simultaneously.
- Strong written and verbal communication skills.
- Ability to influence senior stakeholders through data-driven recommendations.

Preferred Educational Qualification:

- Bachelor's or Master's degree in: Statistics, Mathematics, Computer Science, Engineering, Data Science, Analytics
- MBA is an added advantage.

📌 Lead Data Scientist (Bengaluru)
🏢 MathCo
📍 Bengaluru