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Real World Evidence Rwe Jobs in Basking Ridge, NJ

Tempus

Data Scientist II, Outcomes Research

New York, NY · 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.

Jj

Associate Director, Global MAA & RWE

Raritan, NJ

Learn more at Associate Director, Market Access Analytics and Real World Evidence (MAA & RWE) - Indirect Treatment Comparisons The Associate Director, Market Access Analytics and Real-World Evidence ...

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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 Basking Ridge, NJ? The most popular types of Real World Evidence Rwe jobs in Basking Ridge, NJ are:
What cities near Basking Ridge, NJ are hiring for Real World Evidence Rwe jobs? Cities near Basking Ridge, NJ with the most Real World Evidence Rwe job openings:
Real World Evidence Rwe jobs near you
Data Scientist II, Outcomes Research

Data Scientist II, Outcomes Research

Tempus

New York, NY • On-site, Remote

$100K - $150K/yr

Full-time

Posted 17 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 Tempus and the Outcomes Research Team

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.

The Outcomes Research team partners with external Pharma, biotech, and academic institutions to provide best-in-class data, analysis, and methodological guidance for Tempus's real-world data (RWD) offering. We are seeking a highly motivated and capable Sr. Data Scientist with extensive experience in the design and analysis of pharmacoepidemiologic and health economic outcomes research (HEOR) studies.

Responsibilities:

  • 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.

  • Represent the Outcomes Research function and collaborate with internal and external stakeholders in the design, analysis, interpretation, and publication of real-world studies.

  • Work on complex problems, exercising judgment in selecting and adapting appropriate epidemiologic and health economic methodologies.

  • Partner with interdisciplinary groups of scientists, engineers, and product developers to translate research into clinically actionable insights for our clients.

  • Stay current with the latest methodological advances in RWE, including causal inference and pharmacoepidemiologic methods.

  • Build analytical infrastructure, including reusable code, templates, and workflows that improve speed and quality across engagements.

  • Comply with all applicable regulations, Tempus data governance, and company procedures related to real-world data use and reporting.

Required Experience:

  • Advanced degree (Master's with 2+ years experience or equivalent) in data science, bioinformatics, biostatistics, epidemiology, immunology, public health, or related quantitative field.

  • Demonstrated computational skills using R and SQL, specifically applied to large-scale healthcare datasets.

Preferred Qualifications:

  • Strong data manipulation and analytical skills tailored to observational/real-world data.

  • Deep familiarity with HEOR and RWE methodologies, including approaches to address confounding (e.g., propensity score matching, weighting, inverse probability of treatment weighting).

  • Experience analyzing large, complex real-world datasets, including administrative claims, electronic health records (EHR), and/or clinico-genomic databases.

  • Strong communication and presentation skills with the ability to translate complex methodologies and findings for non-technical stakeholders.

  • Self-driven mindset with demonstrated ability to tackle ambiguous problems and work effectively in interdisciplinary teams.

  • Experience with time-to-event analysis and survival methodologies.

  • Experience working in oncology and/or analyzing outcomes related to cancer genetics, immunology, or molecular biology.

  • Collaborative working style, eagerness to learn, and high-integrity work ethic.

  • Sharp attention to detail and a passion for delivering high-quality, timely analytics.

  • Ability to draw appropriate inferences based on study design and explicitly assess and communicate study limitations.

Nice to have:

  • Experience with version control (e.g., Git) and software testing or validation processes.

  • Experience working in oncology Phase II-IV clinical trials and/or experience with the analysis of RWD and/or HEOR studies (e.g. using claims, EHR or registry data sources).

  • Hands-on experience contributing to regulatory submissions to the FDA or other health authorities.

  • Experience supporting data science teams in model building and validation, including feature engineering and performance assessment.

  • Client-facing or consulting experience and comfort presenting results and recommendations to external stakeholders.

#LI-BL1CHI: $90,000-$135,000NYC/SF: $100,000-$150,000

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.

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