Principal Statistician - Real World Analytics

Lever, Inc.

India

Remote

INR 3,000,000 - 5,500,000

Full time

2 days ago
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Benefits offered by this job

Remote work opportunity

Job summary

Lever, Inc. (on behalf of a partner) is seeking a Principal Statistician - Real World Analytics based in India.

The role provides senior statistical expertise across real-world evidence, medical affairs and observational research initiatives with hands-on programming and strategic input into protocols, analysis plans and study deliverables. You will collaborate with cross-functional teams, develop abstracts, posters, and manuscripts, and apply advanced methods including propensity scores, causal

Qualifications

  • PhD or Master's degree in Biostatistics, Statistics, or a closely related quantitative discipline.
  • Pharmaceutical industry experience providing statistical input into study design, analysis and reporting for interventional and observational studies.
  • At least 4 years of experience on Phase 4, Medical Affairs, Real World Evidence (RWE) or HEOR studies.
  • At least 4 years hands-on experience with statistical programming and analysis using SAS and R.

Responsibilities

  • Provide statistical input into observational study and clinical trial design and development.
  • Author and review statistical analysis plans, TFL shells, and SDTM/ADaM datasets.
  • Support Phase 4 non-interventional and real-world evidence studies.
  • Collaborate with cross-functional teams to develop CRFs, validate datasets, and review analytical results.
  • Conduct statistical programming and analysis for Medical Affairs and RWE studies.
  • Apply advanced statistical approaches including propensity scores, causal inference, and mixed-effects models.
  • Contribute to abstracts, posters, manuscripts, and other scientific deliverables.
  • Ensure analyses are documented and aligned with study objectives.

Skills

Propensity score methods
Causal inference
Mixed-effects models
Machine learning
Statistical programming

Education

PhD or Master's in Biostatistics/Statistics

Tools

SAS
R
SDTM/ADaM

Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Principal Statistician - Real World Analytics based in India.

This role provides senior statistical expertise across real-world evidence, medical affairs, and observational research initiatives. You will contribute to study design, statistical analysis, and reporting, helping transform complex healthcare data into meaningful evidence. The position combines hands‑on statistical programming with strategic input into protocols, analysis plans, datasets, and study deliverables. You will collaborate closely with programming and cross‑functional teams throughout Phase 4 and non‑interventional studies. Your expertise will support the development of abstracts, posters, manuscripts, and other scientific outputs. The role is well suited to an experienced statistician who enjoys applying advanced methodologies to real world healthcare questions.

Accountabilities:
  • Provide statistical expertise and input into the design and development of observational studies and clinical trials.
  • Author and review statistical analysis plans, analysis dataset specifications, and tables, listings, and figures (TFL) shells.
  • Provide statistical support for Phase 4 non-interventional and real‑world evidence studies.
  • Collaborate with programming and cross‑functional teams to develop case report forms, validate datasets, and review analytical results.
  • Conduct statistical programming and analysis for Medical Affairs and real‑world evidence studies using appropriate methodologies.
  • Apply advanced statistical approaches, including propensity score methods, causal inference, mixed‑effects models for repeated measures, and machine learning techniques.
  • Support the interpretation and communication of study findings through abstracts, posters, manuscripts, and other scientific deliverables.
  • Contribute statistical expertise throughout the study lifecycle, ensuring analyses are scientifically sound, appropriately documented, and aligned with study objectives.
Requirements:
  • PhD or Master's degree in Biostatistics, Statistics, or a closely related quantitative discipline.
  • Pharmaceutical industry experience providing statistical input into study design, analysis, and reporting for interventional and observational studies.
  • At least 4 years of experience working on Phase 4 studies, Medical Affairs studies, Real World Evidence (RWE), or Health Economics and Outcomes Research (HEOR) studies.
  • At least 4 years of hands‑on experience with statistical programming and analysis using SAS and R.
  • At least 4 years of experience working with SDTM and ADaM data standards.
  • At least 4 years of experience with Real World Data (RWD) and RWE methodologies, including propensity score analysis and causal inference.
  • At least 4 years of experience applying advanced statistical models, such as mixed‑effects approaches for repeated measures and machine learning methods.
  • Strong understanding of clinical research, observational study methodologies, and pharmaceutical development processes.
  • Strong analytical, problem‑solving, communication, and cross‑functional collaboration skills.
  • Ability to translate complex statistical concepts and findings into clear, scientifically rigorous deliverables.
Benefits:
  • Remote work opportunity.
  • Opportunity to contribute to real‑world evidence and Medical Affairs research within the pharmaceutical industry.
  • Exposure to Phase 4, observational, and clinical research programs.
  • Opportunity to apply advanced statistical methodologies, including causal inference, mixed‑effects models, and machine learning.
  • Collaboration with statistical programmers and multidisciplinary research teams.
  • Opportunity to contribute to scientific publications, abstracts, posters, and manuscripts.
  • Senior‑level exposure to the full lifecycle of real‑world analytics and evidence‑generation projects.
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