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Real World Evidence Rwe Jobs in Elmhurst, IL (NOW HIRING)

About the Role The Key Account Director will own and expand strategic partnerships with MedTech, Pharma, and industry partners engaged in Real-World Evidence (RWE) and data-driven initiatives. You'll ...

Data Scientist II, Outcomes Research

Chicago, IL · On-site +1

$100K - $150K/yr

Lead and execute HEOR and real-world evidence (RWE) projects (e.g., outcomes analysis, treatment patterns, healthcare resource utilization) with external Pharma, academic, and other partners.

About the Role The Key Account Director will own and expand strategic partnerships with MedTech, Pharma, and industry partners engaged in Real-World Evidence (RWE) and data-driven initiatives. You'll ...

Lead and execute HEOR and real-world evidence (RWE) projects (e.g., outcomes analysis, treatment patterns, healthcare resource utilization) with external Pharma, academic, and other partners.

Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real ... Associate Director RWE, PharmaR&D Locations: Boston, MA | New York City, NY | Chicago, IL Are you ...

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Real World Evidence Rwe information

What is the difference between Real World Evidence Rwe vs Clinical Data Analyst?

AspectReal World Evidence RweClinical Data Analyst
Required credentialsTypically requires a background in healthcare, epidemiology, or biostatistics, often with a master's or PhDUsually requires a degree in health informatics, biostatistics, or related fields, with similar certifications
Work environmentPrimarily in healthcare, pharmaceutical, or research organizations analyzing real-world dataIn clinical research settings, hospitals, or pharmaceutical companies analyzing clinical trial data
Employer and industry usageUsed by pharma companies, healthcare providers, and research institutions to generate real-world insightsUsed by research organizations, hospitals, and pharma for clinical trial data management and analysis

Real World Evidence Rwe professionals focus on analyzing data from real-world settings like electronic health records and insurance claims, while Clinical Data Analysts primarily work with clinical trial data. Both roles require strong analytical skills and related credentials, but Rwe specialists emphasize real-world data sources to inform healthcare decisions.

What is the difference between RWE and real-world data?

In the context of a Real World Evidence (RWE) role, real-world data (RWD) refers to the raw data collected from sources like electronic health records, claims databases, and patient registries. RWE is the clinical evidence generated by analyzing and interpreting RWD to inform healthcare decisions, regulatory approvals, and policy making. RWD is the data input, while RWE is the meaningful insights derived from that data through analysis and research methods.

How do you get into RWE?

To enter a role in Real World Evidence (RWE), candidates typically need a background in healthcare, epidemiology, or data science, along with skills in biostatistics and familiarity with electronic health records and real-world data sources. Gaining experience through relevant internships, certifications, or advanced degrees can improve prospects. Proficiency in statistical software and understanding of regulatory requirements are also valuable.

What is Real World Evidence (RWE) in the healthcare industry?

Real World Evidence (RWE) refers to clinical evidence regarding the usage and potential benefits or risks of a medical product, derived from analysis of real-world data (RWD). This data is collected from sources outside of traditional clinical trials, such as electronic health records, insurance claims, patient registries, and wearable devices. RWE plays a crucial role in understanding how treatments work in routine clinical practice, informing regulatory decisions, and supporting drug development and market access. Organizations use RWE to complement clinical trial data, improving healthcare outcomes and patient care.

What are the key skills and qualifications needed to thrive as a Real World Evidence (RWE) professional, and why are they important?

To thrive as a Real World Evidence (RWE) professional, you need a strong background in epidemiology, biostatistics, and data analysis, often supported by an advanced degree in a relevant scientific field. Familiarity with statistical software (such as SAS, R, or Python), real-world data sources (like EHRs and claims databases), and regulatory guidelines (FDA/EMA) is essential. Strong communication, problem-solving, and cross-functional collaboration skills help convey complex findings to stakeholders and integrate RWE into decision-making. These competencies are crucial for generating credible insights that inform clinical, regulatory, and commercial strategies in the healthcare industry.

How does a Real World Evidence (RWE) professional typically collaborate with cross-functional teams in the pharmaceutical industry?

RWE professionals often work closely with colleagues from epidemiology, health economics, medical affairs, and regulatory affairs to design and execute studies using real-world data. Collaboration is essential, as RWE findings support evidence generation for regulatory submissions, market access, and post-marketing surveillance. Regular meetings, data-sharing sessions, and joint project planning are common, ensuring all stakeholders are aligned on study objectives, methodologies, and data interpretation. This collaborative environment helps translate complex data into actionable insights that support decision-making across the organization.

What are examples of real world evidence?

Real World Evidence (RWE) in the context of a role like a Real World Evidence professional involves data collected from sources outside traditional clinical trials, such as electronic health records, insurance claims, patient registries, and wearable devices. These data sources are analyzed to assess treatment effectiveness, safety, and healthcare outcomes in real-world settings, often using statistical and data management tools. RWE helps inform healthcare decisions and regulatory approvals by providing insights from diverse patient populations outside controlled environments.

What is RWE real world evidence?

Real World Evidence (RWE) is data collected from real-world settings such as electronic health records, claims data, and patient registries. In the context of a role like a Real World Evidence (RWE) professional, it involves analyzing this data to support healthcare decision-making, regulatory submissions, and clinical research using statistical tools and data management skills.
What are the most commonly searched types of Real World Evidence Rwe jobs in Elmhurst, IL? The most popular types of Real World Evidence Rwe jobs in Elmhurst, IL are:
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Senior Data Scientist II, Real World Evidence (RWE), Pharma R&D

Senior Data Scientist II, Real World Evidence (RWE), Pharma R&D

Tempus

Chicago, IL • On-site

Full-time

Posted 27 days ago


Job description

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

About the Role:

The Real World Evidence (RWE) group within the Pharma R&D team at Tempus works with major pharmaceutical partners to provide best-in-class data, analysis, and methodological guidance for Tempus's real-world data offering.

We are seeking a highly motivated and solutions-oriented RWE Senior Data Scientist II with experience and interest in oncology and epidemiological study design to join our team. This role requires the ability to lead observational studies, derive insights from complex real-world clinical data, implement advanced statistical methods, and leverage cutting-edge AI tools to scale tasks and augment insights.

Key Responsibilities
  • Pharma Collaboration & Strategy: Partner with pharmaceutical collaborators to independently execute robust RWE research plans that leverage the Tempus multimodal platform to address key questions in trial design and outcomes research.

  • Real World Data Expertise: Lead the derivation of complex real-world endpoints using extensive coding, demonstrating deep comprehension of Tempus clinical and molecular data structures and complexity, while also serving as an expert on the methodological nuances and limitations of real-world data.

  • Methodology & Platform Contribution: Stay up-to-date on methodological advancements in real-world studies (e.g., causal inference, survival analysis) and oncology guidelines (NCCN and ongoing clinical trials) to contribute to reusable code, internal packages, and best practices that can be applied across multiple collaborations.

  • AI & LLM Innovation: Incorporate LLMs, agentic workflows and other AI tools into day-to-day workflows to accelerate code development, discovery, documentation, review, and insight generation.

  • Scientific Interpretation & Communication: Interpret results of RWE analyses to draw appropriate inferences based on study design/statistical methods, while also evaluating study limitations. Communicate complex methods and results clearly to both technical and non-technical stakeholders. Prepare and present internal reports, external-facing deliverables, and, where appropriate, manuscripts or conference materials.

  • Cross-Functional Collaboration: Collaborate with internal product, oncology, and clinical abstraction, and real-world data science teams to continually enhance Tempus data quality, products, and analytical best practices.

Minimum Qualifications
  • Education: Education in epidemiology, biostatistics, data science, public health, or a related field, to the level of either:

    • PhD

    • Master's degree and 2+ years of additional work experience

  • Technical and Statistical Proficiency:

    • Proficiency with observational real-world healthcare data, including analytical experience with time-to-event methodologies (survival analysis).

    • Proven expertise in executing RWD analytical studies.

    • Proficient in using R and SQL, especially statistical tools and packages.

    • Proficiency applying machine learning, LLM-based coding assistants (e.g., Copilot, Cursor) and agentic frameworks to support data analysis, code review, or scientific documentation workflows.

    • Adherence to good software engineering practices (version control, modular code, documentation).

  • Communication & Client Focus: Demonstrated experience interfacing with clients, showcasing adeptness in presenting and tailoring messaging to a variety of stakeholders.

  • Soft Skills: Excellent written and verbal communication skills with strong project management skills. Ability to thrive in a fast-paced, dynamic environment working with multi-disciplinary scientists on complex problems.

Preferred Skillsets
  • Experience working with Pharma or drug development.
  • Experience in clinical trial design (particularly Phase II-III) in the clinical development space.

  • Analytical proficiency with claims, EHR, or registry data.

  • Practical experience configuring or adapting LLMs, or using related tools/frameworks, to support scientific work.

  • Knowledge of oncology guidelines (e.g., NCCN).

  • Experience with biomarker or molecular data (e.g., genomics).

  • Experience with cloud platforms such as AWS and/or BigQuery and/or Google Cloud Platform (GCP).

The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.

Additionally,for remote roles open to individuals in unincorporated Los Angeles - including remote roles-Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.