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Data Science with Real-World Evidence (RWE) Analyst
Client based at Bangalore location.
Data Science with Real-World Evidence (RWE) Analyst
Client based at Bangalore location.'s logo

Data Science with Real-World Evidence (RWE) Analyst

at Client based at Bangalore location.

4 - 20 yrs
₹12L - ₹30L / yr
Remote only
Skills
skill iconData Science
Real world evidance
RWE analyst
Healthcare

Role Summary

We are seeking a highly motivated and skilled Data Science with Real-World Evidence (RWE) Analyst to join our dynamic team. This role is at the intersection of advanced data analytics and real-world data, focusing on extracting meaningful insights from diverse healthcare datasets to inform strategic decisions, support clinical development, and demonstrate product value. The ideal candidate will possess a strong foundation in data science methodologies, statistical analysis, and a deep understanding of real-world healthcare data sources and their application in evidence generation.

Key Responsibilities

  • Data Acquisition & Preparation: Identify, access, and prepare large, complex real-world datasets (e.g., electronic health records, claims data, patient registries, wearable device data) for analysis, ensuring data quality, consistency, and privacy compliance.
  • Methodology & Analysis: Apply advanced statistical methods, machine learning algorithms, and data mining techniques to real-world data to answer specific research questions related to disease progression, treatment patterns, patient outcomes, drug safety, and comparative effectiveness.
  • Study Design & Protocol Development: Collaborate with RWE scientists, epidemiologists, and clinical teams to design robust RWE studies, develop analytical protocols, and ensure methodological rigor.
  • Insight Generation & Interpretation: Interpret complex analytical results, derive actionable insights, and identify trends or patterns within real-world data.
  • Reporting & Visualization: Develop clear, concise, and compelling reports, presentations, and interactive dashboards to communicate complex analytical findings to diverse stakeholders (e.g., clinical, commercial, regulatory, research & development teams).
  • Tool & Model Development: Build and maintain analytical tools, models, and pipelines to automate data processing and analytical workflows, ensuring scalability and reproducibility.
  • Collaboration: Work cross-functionally with biostatisticians, epidemiologists, clinicians, IT professionals, and business stakeholders to translate scientific questions into analytical plans and deliver impactful RWE.
  • Documentation & Compliance: Ensure all analyses adhere to relevant regulatory guidelines, ethical considerations, and internal SOPs. Maintain thorough documentation of data sources, methodologies, and results.
  • Innovation: Stay abreast of the latest advancements in data science, RWE methodologies, and healthcare analytics, continuously seeking opportunities to apply novel techniques.

Qualifications

Required:

  • Education: Master's or Ph.D. in Data Science, Statistics, Biostatistics, Epidemiology, Computer Science, Health Informatics, or a related quantitative field.
  • Experience:
  • Minimum of 4-20 years of professional experience in data science, analytics, or a related role, with a significant focus on real-world data (RWD) or real-world evidence (RWE) in the healthcare or life sciences industry.
  • Proven experience working with large-scale, complex healthcare datasets (e.g., claims data, EHRs, patient registries).
  • Technical Skills:
  • Proficiency in statistical programming languages (e.g., Python, R) and their associated data science libraries (e.g., pandas, NumPy, scikit-learn, ggplot2, tidyverse).
  • Strong SQL skills for data extraction, manipulation, and querying large databases.
  • Experience with data visualization tools (e.g., Tableau, Power BI, Shiny, matplotlib, seaborn).
  • Solid understanding of statistical modeling techniques (e.g., regression, survival analysis, causal inference methods) and machine learning algorithms (e.g., classification, clustering, time series).
  • Domain Knowledge: Foundational understanding of healthcare data structures, medical coding systems (ICD, CPT, NDC), and pharmaceutical development lifecycle.

Preferred:

  • Experience with cloud computing platforms (e.g., AWS, Azure, GCP) and big data technologies (e.g., Spark, Databricks).
  • Familiarity with distributed version control systems (e.g., Git).
  • Prior experience in observational research, epidemiology, or health economics and outcomes research (HEOR).
  • Publications in peer-reviewed journals or presentations at scientific conferences related to RWE or data science in healthcare.

Skills

  • Excellent analytical and problem-solving skills with meticulous attention to detail.
  • Strong communication and presentation skills, with the ability to convey complex technical concepts to non-technical audiences.
  • Ability to work independently and collaboratively in a fast-paced, multidisciplinary environment.
  • Intellectual curiosity and a passion for leveraging data to solve real-world healthcare challenges.
  • High ethical standards and a commitment to data privacy and responsible data use.



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Shubham Vishwakarma

Full Stack Developer - Averlon
I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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Shubham Vishwakarma

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I had an amazing experience. It was a delight getting interviewed via Cutshort. The entire end to end process was amazing. I would like to mention Reshika, she was just amazing wrt guiding me through the process. Thank you team.
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