Real-World Evidence (RWE) Analyst / Senior RWE Analyst at Client based at Bangalore location. · Remote only · 4 - 20 years · ₹12L - ₹30L / yr · Remote only · Posted 17 Jun 2025

Real-World Evidence (RWE) Analyst / Senior RWE Analyst
at Client based at Bangalore location.
Position Overview:
We are seeking a highly motivated and skilled Real-World Evidence (RWE) Analyst to join growing team. The successful candidate will be instrumental in generating crucial insights from real-world healthcare data to inform decision-making, improve patient outcomes, and advance medical understanding. This role offers an exciting opportunity to work with diverse healthcare datasets and contribute to impactful research that drives real-world change.
Key Responsibilities:
For Both RWE Analyst (Junior) & Senior RWE Analyst:
- Data Expertise: Work extensively with real-world healthcare data, including Electronic Medical Records (EMR), claims data, and/or patient registries. (Experience with clinical trial data does not fulfill this requirement.)
- Methodology: Apply appropriate statistical and epidemiological methodologies to analyze complex healthcare datasets.
- Communication: Clearly communicate findings through presentations, reports, and data visualizations to both technical and non-technical audiences.
- Collaboration: Collaborate effectively with cross-functional teams, including clinicians, epidemiologists, statisticians, and data scientists.
- Quality Assurance: Ensure the accuracy, reliability, and validity of all analyses and reports.
- Ethical Conduct: Adhere to all relevant data privacy regulations and ethical guidelines in real-world data research.
Specific Responsibilities for RWE Analyst (Junior):
- Perform statistical analysis on real-world healthcare datasets under guidance.
- Contribute to the development of analysis plans, often by implementing predefined methodologies or refining existing approaches.
- Prepare and clean data for analysis, identifying and addressing data quality issues.
- Assist in the interpretation of study results and the drafting of reports or presentations.
- Support the preparation of journal publication materials based on RWE studies.
Specific Responsibilities for Senior RWE Analyst:
- Analysis Design & Leadership: Independently design and develop comprehensive analysis plans from inception for RWE studies, identifying appropriate methodologies, data sources, and analytical approaches. This role requires a "thinker" who can conceptualize and drive the analytical strategy, not just execute pre-defined requests.
- Project Management: Lead and manage RWE projects from conception to completion, ensuring timely delivery and high-quality outputs.
- Mentorship: Mentor and guide junior RWE analysts, fostering their development in real-world data analysis and research.
- Methodological Innovation: Proactively identify and evaluate new methodologies and technologies to enhance RWE capabilities.
- Strategic Input: Provide strategic input on study design, data acquisition, and evidence generation strategies.
Qualifications:
For Both RWE Analyst (Junior) & Senior RWE Analyst:
- Bachelor's or Master's degree in Epidemiology, Biostatistics, Public Health, Health Economics, Data Science, or a related quantitative field. (PhD preferred for Senior RWE Analyst).
- Demonstrable hands-on experience working with real-world healthcare data, specifically EMR, claims, and/or registry data. Clinical trial data experience will not be considered as meeting this requirement.
- Proficiency in at least one statistical programming language (e.g., R, Python, SAS, SQL).
- Strong understanding of epidemiological study designs and statistical methods relevant to RWE.
- Excellent analytical, problem-solving, and critical thinking skills.
- Strong written and verbal communication skills.
Specific Qualifications for RWE Analyst (Junior):
- 4+ years of experience in real-world data analysis in a healthcare or pharmaceutical setting.
- Involvement with journal publications is highly desirable. (e.g., co-authorship, contribution to manuscript preparation).
Specific Qualifications for Senior RWE Analyst:
- 5+ years of progressive experience in real-world data analysis, with a significant portion dedicated to independent study design and leadership.
- A strong track record of journal publications is essential. (e.g., lead author, significant contribution to multiple peer-reviewed publications).
- Proven ability to translate complex analytical findings into actionable insights for diverse stakeholders.
- Experience with advanced analytical techniques (e.g., machine learning, causal inference) is a plus.
Preferred Skills (for both roles, but more emphasized for Senior):
- Experience with large healthcare databases (e.g., IQVIA, Optum, IBM MarketScan, SEER, NDHM).
- Knowledge of common data models (e.g., OMOP CDM).
- Familiarity with regulatory guidelines and best practices for RWE generation.

Similar jobs (2)
About the Company:
WebMD Health Corp., an Internet Brands Company, is the leading provider of health information services, serving patients, physicians, health care professionals, employers, and health plans through our public and private online portals, mobile platforms, and health-focused publications. The WebMD Health Network includes WebMD Health, Medscape, Jobson Healthcare Information, prIME Oncology, MediQuality, Frontline, QxMD, Vitals Consumer Services, MedicineNet, eMedicineHealth, RxList, OnHealth, Medscape Education, and other owned WebMD sites. WebMD®, Medscape®, CME Circle®, Medpulse®, eMedicine®, MedicineNet®, theheart.org®, and RxList® are among the trademarks of WebMD Health Corp. or its subsidiaries. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or veteran status.
For Company details, visit our website: www.webmd.com
Experience: 3+ years
Qualification: Master's degree in Computer Science, Statistics, Mathematics, or a related field.
Work Timings: 2 PM to 11 PM IST
Position Requirement:
- Write clean and efficient code in Python and/or R for data analysis, statistical modeling, and machine learning tasks.
- Apply statistical and machine learning techniques to analyze large datasets and extract meaningful patterns, trends, and insights. Develop and implement predictive models for various business applications.
- Formulate hypothesis tests and design experiments to validate assumptions, measure the impact of changes, and optimize decision-making processes.
- Demonstrate strong SQL skills for efficient data querying and manipulation using window functions.
- Work with large datasets and ensure data quality and accuracy.
- Experience with dashboarding tools like Tableau is a plus to visualize and present data-driven insights to both technical and non-technical stakeholders.
- Ability to communicate complex technical concepts and insights in a clear and concise manner to both technical and non-technical audiences. Engage with the leadership team and clients to understand business requirements and provide data-driven solutions.
- Work with real world case studies in Data Science and a chance to implement various modelling techniques. Opportunity to independently execute and lead analytical projects and assignments.
- Help solve some challenging Healthcare related digital marketing problems globally. Transform business question into data requirements; collect and merge the data; analyse the data, link it to the business reality and present the results
- Develop predictive models and machine learning algorithms to study change in physician prescribing behaviour as well as WebMD integrated campaign response behaviour. Build analysis to understand user engagement and behaviours across various WebMD products.
Technical Skills needed:
1.Experience with data manipulation in SQL environment is a must. Experience with BigQuery/Vertica data warehousing is good to have
- Experience with statistical and data manipulation tools such as Python or R is a must
- Need very good expertise in using Microsoft Excel, and Microsoft PowerPoint. Excellent presentation skills required
- Experience developing statistical models like hypothesis testing, regression models, classifications models, forecasting etc is a must
- Algorithm designing and implementation skills in R or Python is required
Requirements
- B.Tech/B.E. / MSc Statistics from premier institutes with
- Minimum 80% marks in 10th and 12th
- Minimum 75% marks in graduation
- 2-5 years of relevant work experience in analytics field
- Proven experience in data science, statistical modeling, and machine learning applications.
- Strong proficiency in Python and/or R programming languages.
- Solid understanding of statistical concepts, hypothesis testing, and experimental design
- Expertise in SQL for data querying and manipulation.
- Familiarity with dashboarding tools is a plus.
- Excellent presentation, communication and interpersonal skills.
We’re looking for a dynamic and driven Data Analyst to join our team of technology enthusiasts. This role is crucial in transforming data into insights that support strategic decision-making and innovation within the insurance technology (InsurTech) space. If you’re passionate about working with data, understanding systems, and delivering value through analytics, we’d love to hear from you.
What We’re Looking For
- Proven experience working as a Data Analyst or in a similar analytical role
- 5+ Years of experience in the field
- Strong command of SQL for querying and manipulating relational databases
- Experience with Power BI for building impactful dashboards and reports
- Familiarity with QlikView and Qlik Sense is a plus
- Ability to communicate findings clearly to technical and non-technical stakeholders
- Knowledge of Python or R for data manipulation is nice to have
- Bachelor’s degree in Computer Science, Statistics, Mathematics, Economics, or a related field
- Understanding of the insurance industry or InsurTech is a strong advantage
What You’ll Be Doing:
- Delivering timely and insightful reports to support strategic decision-making
- Working extensively with Policy Administration System (PAS) data to uncover patterns and trends
- Ensuring data accuracy and consistency across reports and systems
- Collaborating with clients, underwriters, and brokers to translate business needs into data solutions
- Organizing and structuring datasets, contributing to data engineering workflows and pipelines
- Producing analytics to support business development and market strategy








