Functional Consultant – Pharma RWE Epidemiology & Observational Science

Job Title :

Functional Consultant – Pharma RWE Epidemiology & Observational Science

Experience : 6–10 years

Industry :

Pharmaceutical / Biotechnology

Location : Bangalore

Employment Type : Full-Time

Overview

Our client – one of the largest data science companies – is seeking to hire a

Functional Consultant – Life Sciences

with 6–10 years of experience in the pharmaceutical or biotechnology industry, specifically within pre-clinical and / or clinical research and development (R&D).

The ideal candidate will have a strong foundation in managing scientific research projects, coordinating cross-functional teams, and collaborating with global stakeholders across geographies. Demonstrated experience in project execution, scientific communication, and data-driven decision-making is essential.

The ideal candidate will embrace the Company’s

Decision Sciences Lifecycle

and ways of working, acting as a strategic transformation partner to drive long-term business, financial, and operational outcomes. They will leverage advanced analytics, machine learning, statistical modeling, and a global delivery model to build data-driven solutions.

The role involves shaping growth strategies, identifying new business opportunities, and applying design thinking for structured problem-solving. Candidates should deliver actionable insights through compelling data visualizations, reports, and presentations, while also monitoring solution performance and ensuring continuous optimization. Leadership of offshore teams, including onboarding, mentoring, and performance management, is a key responsibility.

Domain Expertise

Candidates must have hands-on experience or exposure to

at least one

of the following functional domains :

Epidemiological Study Design & Analysis

Expertise in designing and conducting epidemiological studies, including cohort, case-control, cross-sectional, and longitudinal studies

Proficiency in statistical methods for epidemiological data analysis, such as regression modeling, survival analysis, and propensity score matching

Experience with tools like SAS, R, or Stata for analyzing epidemiological datasets and generating actionable insights

Knowledge of bias identification, confounding adjustment, and causal inference methodologies in observational studies

Familiarity with regulatory requirements (e.g., FDA, EMA) for epidemiological data used in drug safety and efficacy evaluations

Real-World Evidence (RWE) & Health Outcomes Research

Experience in leveraging real-world data (RWD) sources, such as electronic health records (EHRs), claims databases, and registries, to generate RWE

Proficiency in health outcomes research, including patient-reported outcomes (PROs), quality-of-life assessments, and cost-effectiveness analyses

Knowledge of advanced analytics for RWE, including machine learning for predictive modeling of disease progression or treatment outcomes

Familiarity with standards like OMOP CDM (Common Data Model) and tools like SQL or Python for RWD processing

Expertise in supporting post-marketing surveillance and pharmacoepidemiology studies for regulatory submissions

RWE Epidemiology / Observational Research

Important Requirements :

Expertise in designing and executing epidemiological studies to generate real-world evidence (RWE), including natural history of disease, population characterization, treatment patterns, unmet needs, external comparators, clinical outcome benchmarking, and comparative safety / effectiveness research

Experience developing and managing study protocols, statistical analysis plans (SAPs), and study reports under scientific oversight to address priority RWE research questions

Proficiency in constructing cohorts using real-world data (RWD) sources (e.g., claims, EHRs, patient-reported outcomes, registries) and evaluating key variables, including diagnosis and procedure codes, with validation study planning

Knowledge of observational research methods (primary and secondary data collection) and biostatistics for descriptive and comparative analyses

Experience contributing to regulatory documents, publications, white papers, abstracts, or manuscripts for external dissemination of observational research results

Record of coauthoring scientific publications demonstrating expertise in observational study design, analysis, and interpretation

Ability to support internal and external decision-making, including rapid analyses for safety queries and responses to regulatory authorities (e.g., FDA, EMA)

Strong project management skills to deliver studies within time, budget, and quality standards, with increasing autonomy in a matrix environment

Additional Desirable Requirements :

Familiarity with identifying fit-for-purpose RWD sources to support timely execution of RWE strategies

Experience in developing processes or training to enhance the efficiency, quality, and impact of RWE epidemiology activities

Knowledge of biomarker or data science project design in the context of observational research

Additional Competencies

Additional competencies in data science and analytics using R, Python, or SQL, along with familiarity with Agile methodologies, JIRA, and other project management tools, are considered strong advantages. Experience with AI / ML tools, data visualization platforms (e.g., Tableau, Power BI), and working in cross-disciplinary environments will be a plus.