Senior Data Analyst – Patient Journey & LOT Analytics - Remote

Overview

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.

In Short

• 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.
• Ensure data integrity, governance, documentation and reproducibility.
• Independently manage workload, communicate progress and drive project delivery.

Requirements

• 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.