Senior Data Analyst

Role overview

This opportunity is for a partner organization, which will handle all applications and the next stages of the hiring process. The company is seeking a Senior Data Analyst who is based in India and can work remotely.

In this role, you will turn complex healthcare and oncology data into insights that help shape strategic decisions across pharmaceuticals and life sciences. You will work with large claims and patient-level datasets to study treatment journeys, line-of-therapy trends, and real-world evidence outcomes. The position is highly analytical and client-facing, with direct impact on market access, HEOR work, and commercial planning. You will partner with teams across data engineering, consulting, and strategy, and you will need to present findings clearly to both technical and non-technical audiences.

Key responsibilities

• Take ownership of analytics workstreams centered on oncology patient pathways, line-of-therapy analysis, and brand performance using large healthcare datasets.
• Use exploratory analysis to uncover treatment patterns, usage trends, and clinical pathways seen in real-world data.
• Work with complex claims sources such as DRG, IQVIA, McKesson, and Symphony to derive practical business insights.
• Contribute to HEOR and HCRU studies, including work on incidence, prevalence, cost of illness, and overall disease burden.
• Create, improve, and automate data pipelines and SQL logic, while using Python and Excel for deeper analytical work.
• Prepare dashboards and presentation-ready outputs in PowerPoint and visualization tools to communicate findings effectively.
• Coordinate with cross-functional stakeholders to define the analysis approach, resolve questions, and deliver outputs on time.
• Maintain strong standards for data quality, governance, documentation, and reproducibility across all deliverables.

Experience and background

• You should have 5+ years of total experience, including at least 3+ years in data analytics within healthcare, pharma, or life sciences.
• A bachelor’s or master’s degree in Computer Science, Statistics, Data Science, Life Sciences, Pharmacy, Engineering, or a related discipline is required.
• Hands-on exposure to structured healthcare data sources such as DRG, IQVIA, McKesson, or Symphony claims is important.
• You need advanced working knowledge of SQL, Python, Excel, and PowerPoint for analysis and reporting.
• You should understand real-world evidence sources such as EHR/EMR and CMS datasets.
• Familiarity with line-of-therapy methods, treatment guidelines, and healthcare market access structures is expected.
• Experience in pharma consulting, analytics firms, or life sciences data environments is preferred.
• Strong communication skills are essential, especially the ability to explain complex data clearly to clients and business stakeholders.

Benefits and workplace support

• Competitive pay aligned with your background and current industry norms.
• Remote work flexibility from within India.
• Health insurance and broader medical coverage.
• Paid leave, including vacation, sick leave, and public holidays.
• Support for professional growth and learning.
• Exposure to global healthcare datasets and high-impact oncology analytics projects.
• A collaborative environment with cross-functional and international stakeholders.
• Access to tools and resources that support analysis, visualization, and productivity.

Hiring and privacy information

Applications are screened through an AI-assisted matching process so the strongest-fit candidates can be reviewed quickly and fairly against the role’s core requirements. The resulting shortlist is shared with the hiring company, and interviews or assessments are then managed directly by their internal team.

By applying, you acknowledge that your personal data may be processed to evaluate your candidacy and shared with the hiring employer in line with applicable data protection laws, including GDPR. You may request access, correction, deletion, or objection at any time.

AI tools may be used to support parts of the recruitment workflow, such as application review, resume analysis, response assessment, or detecting possible inconsistencies in submitted information. These tools assist the recruitment team and do not replace human judgment; final hiring decisions are made by people.