Associate Director Real World Analytics

The Lotus Group LLC; United States; On-site; USD 140,000 - 190,000; Full time

Job summary

The Lotus Group LLC is seeking an Associate Director, Real World Analytics to lead programming on oncology real world studies from kickoff through final outputs. You will collaborate with RWE and HEOR scientists, epidemiologists, biostatisticians, and data scientists to translate questions into analysis specs and deliver results.

Responsibilities include leading analyses, authoring datasets and validation plans, constructing cohorts from EHR/claims data, applying survival and propensity score

Qualifications

• BS or MS in statistics, biostatistics, epidemiology, computer science, data science, or mathematics.
• 8+ years of programming experience in real world data, observational research, or related analytics.
• Proficiency in SQL, plus SAS, R, or Python.
• Direct experience with EHR and claims data, including Optum and comparable assets.
• Demonstrated experience leading real world studies end to end as the primary programmer, from specification through final deliverables.
• Working knowledge of observational study design and analytic methods for real world data.
• Established QC and validation practices.

Responsibilities

• Lead programming on assigned oncology real world studies, including treatment patterns, burden of illness, comparative effectiveness and safety, natural history, and external control arm analyses
• Author analysis dataset specifications, TLF shells, and validation plans
• Construct cohorts from EHR, claims, and linked clinical genomic data, including index date and endpoint definitions
• Implement statistical methods including survival analysis, propensity score methods, confounding adjustment, and sensitivity analyses
• Produce and validate tables, listings, and figures for internal, publication, and external use
• Maintain programming documentation, QC records, and traceability across the study lifecycle
• Develop reusable macros, codelists, and standardized frameworks to support team efficiency
• Provide technical guidance to junior programmers

Skills

Leadership

Analytical thinking

Communication

Quality control

Education

BS or MS in statistics/biostatistics/epidemiology/CS/data science/math

Tools

SQL

SAS

R

Python

Job description

The Associate Director, Real World Analytics serves as lead programmer on assigned real world studies, owning delivery from kickoff through final outputs. This role partners directly with RWE and HEOR scientists, epidemiologists, biostatisticians, and data scientists to translate research questions into analysis specifications and deliver the results. This is an individual contributor role.

Responsibilities

• Lead programming on assigned oncology real world studies, including treatment patterns, burden of illness, comparative effectiveness and safety, natural history, and external control arm analyses
• Author analysis dataset specifications, TLF shells, and validation plans
• Construct cohorts from EHR, claims, and linked clinical genomic data, including index date and endpoint definitions
• Implement statistical methods including survival analysis, propensity score methods, confounding adjustment, and sensitivity analyses
• Produce and validate tables, listings, and figures for internal, publication, and external use
• Maintain programming documentation, QC records, and traceability across the study lifecycle
• Develop reusable macros, codelists, and standardized frameworks to support team efficiency
• Provide technical guidance to junior programmers

Qualifications

• BS or MS in statistics, biostatistics, epidemiology, computer science, data science, or mathematics
• 8 or more years of programming experience in real world data, observational research, or related analytics
• Proficiency in SQL, plus SAS, R, or Python
• Direct experience with EHR and claims data, including Optum and comparable assets
• Demonstrated experience leading real world studies end to end as the primary programmer, from specification through final deliverables
• Working knowledge of observational study design and analytic methods for real world data
• Established QC and validation practices

Preferred Qualifications

• Oncology real world evidence experience
• HTA, market access, indirect treatment comparison, or regulatory grade RWE experience
• Experience with genomic or linked clinical genomic datasets
• OMOP CDM experience
• Git, version control, and reproducible workflow practices