The Manager, HEOR Analytics is a key member of the HEOR and Commercial Analytics team within the PrecisionQ business unit. This role is responsible for generating real-world insights using large healthcare datasets to support pharmaceutical, biotechnology, and healthcare provider organizations.
The individual will work with de-identified electronic medical record (EMR), claims, pharmacy, and genomic datasets to develop analytics that inform healthcare decision-making, support value demonstration, and improve understanding of patient outcomes.
This position focuses on applying advanced healthcare analytics to generate insights that support value-based care, oncology research, and real-world evidence generation.
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Assists in the creation of data-driven insights for Pharma, Biotech and healthcare providers organizations.
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Collaborates closely with the software teams to transform claims; electronic health record, pharmacy dispensing, patient-reported outcomes, primary market research and other source data types into high value information/knowledge to satisfy required project output for pharmaceutical, diagnostics, device manufacturers.
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Performs data preparation, cleansing, and application of business rules to ensure analytical datasets accurately represent real-world treatment patterns.
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Conducts analyses describing outcomes, treatment patterns, lines of therapy, and variability in clinical practice.
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Typical engagements involve the measurement of the value of healthcare interventions on outcomes.
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The Manager may attend key (scientific/medical) conferences; identify emerging trends; contribute to publications and collaboratively support the expansion of PQ HEOR.
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Conducts and supports scientific projects culminating in scientific abstracts and peer reviewed papers.
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Bachelor’s degree in statistics, data science, health sciences, economics, epidemiology, or a related quantitative field. Master’s degree preferred.
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2+ years of experience in healthcare analytics, health services research, outcomes research, real-world evidence (RWE), or a related analytical function.
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Foundational knowledge of oncology disease areas, treatment paradigms (e.g., chemotherapy, immunotherapy, targeted therapy), and clinical outcomes research.
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Experience working with healthcare datasets, including claims, EMR/EHR data, laboratory data, or other real-world data sources.
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Proficiency in data analysis and statistical programming tools such as SQL, R, Python, SAS, or similar platforms.
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Ability to perform descriptive and survival analyses (e.g., Kaplan–Meier) and interpret findings in a clinical or research context.
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Experience using data visualization and business intelligence tools (e.g., Power BI, Tableau, Qlik).
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Strong analytical, problem-solving, and data interpretation skills with attention to detail
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Experience contributing to scientific publications, conference abstracts, or technical reports.
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Ability to support development of Methods and Results sections for scientific manuscripts, abstracts, or internal research deliverables.
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Strong SQL experience with the ability to extract, transform, and analyze large datasets from relational databases.
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Experience with healthcare data models and standards, such as OMOP, SDTM, or similar frameworks.
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Experience conducting real-world evidence or observational research, including cohort creation and outcomes analyses.
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Familiarity with cloud computing environments (Azure, AWS, or similar platforms).
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Exposure to machine learning or predictive modeling approaches in healthcare analytics.
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Experience with genomics, biomarker, or precision medicine datasets is a plus.
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Understanding of clinical oncology practice and treatment decision pathways, particularly in interpreting healthcare data.
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Strong written and verbal communication skills with the ability to translate analytical results into actionable insights.
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Proactive and intellectually curious with a strong desire to learn.
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Collaborative team player who thrives in cross-functional environments.
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Creative problem solver with the ability to work in a fast-paced, data-driven organization.
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High level of professionalism, accountability, and attention to quality.
