Senior Data Science Analyst

Senior Data Analyst – Patient Journey & LOT Analytics

Role Summary

We are seeking a motivated, experienced Senior Data Analyst who will lead analytics efforts around Oncology patient journey, line of therapy (LoT) and structured claims/patient data.

The successful candidate will transform large claims datasets into insights that shape strategic decisions for our clients.

Key Responsibilities

Lead and execute analytics projects focused on patient-journey and line-of-therapy mapping.

Analyze structured claims and patient datasets such as DRG, IQVIA, McKesson, Symphony claims.

Conduct exploratory data analysis (EDA) to assess treatment patterns, pathways and utilization.

Support HEOR/HCRU analyses including prevalence, burden, incidence and cost-of-illness studies.

Develop and present client-facing insights using dashboards, PowerPoint and visual analytics.

Build and optimise SQL queries, pipelines; use Excel and Python for automation and analysis.

Collaborate with HEOR, market-access, strategy and engineering teams. Ability to gather requirements, articulate approach, timeline and execution with key stakeholders are of equal importance.

Ensure data integrity, governance, documentation and reproducibility.

Independently manage workload, communicate progress and drive project delivery.

Required Qualifications

Minimum 5 years' experience, with 3+ years in relevant analytics roles.

Bachelor's/Master's in Computer Science, Electronics, Pharmacy, Life Sciences, Data Science, Statistics or related field.

Prior Experience with structured datasets: DRG, Symphony, IQVIA, McKesson.

Strong proficiency in SQL, Python, Excel, PowerPoint.

Experience in Pharma/life-science consulting or analytics agencies.

Exposure to RWE sources including EHR/EMR, CMS datasets.

Understanding of LoT frameworks, treatment guidelines and market-access structures.

Preferred / Nice To Haves

Working knowledge of Python and visualisation tools (Power BI, Tableau).

understanding of data modeling and statistical techniques.

Client-facing experience with ability to translate analytics into business insights.

Therapy-area familiarity (oncology, immunology, rare diseases).

Experience conducting stakeholder workshops or building interactive dashboards.

Experience working with global teams and multi-geography datasets.

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