Data Sciences Sr Mgr

Amgen; Hyderabad; On-site; INR 1,700,000 - 2,200,000; Full time

Job summary

A global biopharmaceutical company in Hyderabad seeks a Commercial Data Science Delivery Lead to drive commercial analytics within assigned Therapeutic Areas. This senior role requires a strong leader to translate complex business challenges into actionable insights, ensuring analytics are integrated into business strategies. Candidates should have 10–15 years in data science, especially within pharma or healthcare, with proficiency in predictive modeling and stakeholder engagement. A successful team leader will cultivate accountability and deliver measurable business impact.

Qualifications

• 10–15 years of experience in data science or advanced analytics.
• Proven experience in analytics delivery within pharmaceutical or healthcare sectors.
• Expertise in predictive modeling and machine learning.

Responsibilities

• Own the analytics agenda for assigned Therapeutic Area.
• Partner with cross-functional teams for data science delivery.
• Lead and mentor a team of data scientists.

Skills

Predictive modeling

Machine learning

Analytical rigor

Stakeholder influence

Job description

How Might You Defy Imagination?

At Amgen, commercial data science shapes how therapies reach patients. It informs targeting, engagement strategy, resource allocation, and measurement of impact.

As a Commercial Data Science Delivery Lead, you will own the analytics agenda for a Therapeutic Area (TA) and be accountable for translating data science into measurable commercial outcomes.

This is a senior leadership role for someone who can bridge business strategy and advanced analytics — ensuring the right problems are solved and insights drive action.

The Role

You will serve as the single point of accountability for commercial data science delivery within your assigned TA(s), partnering with cross-functional Global Customer Capabilities and Innovation (GCCI) teams and leading a team of data scientists to drive business impact.

Key Responsibilities

Commercial & Analytics Leadership

• Define and execute the TA commercial analytics roadmap aligned to strategic priorities.
• Translate complex business questions into structured analytical problem statements.
• Prioritize initiatives based on impact, feasibility, and value realization.
• Represent data science in TA and GCCI governance forums.
• Ensure insights are decision-ready and embedded into commercial execution.

Advanced Analytics & Modeling Oversight

• Lead delivery of patient and HCP analytics, including:
  • Journey and cohort analyses
  • Segmentation and targeting strategies
  • Engagement effectiveness and persistence insights
  • Trigger/alert and identification models
• Oversee predictive modeling, machine learning, and causal measurement approaches.
• Ensure robust validation, lift assessment, and experimental rigor.
• Challenge model assumptions and outputs to maintain scientific credibility.

Measurement & Commercial Effectiveness

• Establish structured measurement frameworks for campaign and engagement impact.
• Guide test-and-learn approaches, including holdouts and quasi-experimental designs.
• Align measurement outputs with broader commercial performance metrics and business KPIs.

Operationalization & Governance

• Partner with engineering and platform teams to deploy and monitor models.
• Ensure documentation, reproducibility, and governance standards are met.
• Implement monitoring strategies for model performance and lifecycle management.

Team Leadership

• Lead and mentor a team of data scientists aligned to the TA.
• Set standards for analytical rigor, business relevance, and delivery excellence.
• Build a culture of accountability, ownership, and continuous improvement.

What Success Looks Like

• A clear, impact-driven analytics roadmap tied to commercial outcomes.
• Analytics integrated into targeting, engagement, and investment decisions.
• Strong trust with GCCI and TA leadership.
• A high-performing data science team delivering consistent business value.
• Measurable improvement in commercial effectiveness and ROI.

Basic Qualifications

• 10–15 years of experience in data science, advanced analytics, or commercial analytics leadership.
• Demonstrated experience driving analytics delivery in pharmaceutical, healthcare, or other commercial industries (e.g., retail, consumer, financial services, tech).
• Strong experience in predictive modeling, machine learning, and/or causal inference (hands-on or through technical oversight).

Preferred Qualifications

• Experience working with healthcare or real-world longitudinal datasets (claims, EMR, specialty pharmacy).
• Exposure to experimental design, uplift modeling, or structured test-and-learn frameworks.
• Experience operationalizing models into production environments.
• Strong executive communication and stakeholder influence skills.
• Experience owning analytics roadmaps for brands, portfolios, or business units