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Real World Evidence Rwe Jobs in Basking Ridge, NJ

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 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:

Associate Director, R&D Neuroscience Data, Data Science & AI - Ophthalmology

Jj

Raritan, NJ • On-site, Remote

$60K - $60K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 22 days ago


Job description

At Johnson & Johnson,we believe health is everything. Our strength in healthcare innovation empowers us to build aworld where complex diseases are prevented, treated, and cured,where treatments are smarter and less invasive, andsolutions are personal.Through our expertise in Innovative Medicine and MedTech, we are uniquely positioned to innovate across the full spectrum of healthcare solutions today to deliver the breakthroughs of tomorrow, and profoundly impact health for humanity.Learn more at jnj.com.

As guided by Our Credo, Johnson & Johnson is responsible to our employees who work with us throughout the world. We provide an inclusive work environment where each person is considered as an individual. At Johnson & Johnson, we respect the diversity and dignity of our employees and recognize their merit.

Job Function:

Data Analytics & Computational Sciences

Job Sub Function:

Data Science Portfolio Management

Job Category:

Professional

All Job Posting Locations:

Cambridge, Massachusetts, United States of America, Raritan, New Jersey, United States of America, San Diego, California, United States of America, Spring House, Pennsylvania, United States of America, Titusville, New Jersey, United States of America

Job Description:

Our expertise in Innovative Medicine is informed and inspired by patients, whose insights fuel our science-based advancements. Visionaries like you work on teams that save lives by developing the medicines of tomorrow.

Join us in developing treatments, finding cures, and pioneering the path from lab to life while championing patients every step of the way.

Learn more athttps://www.jnj.com/innovative-medicine

Johnson & Johnson Innovative Medicine is recruiting for Associate Director, R&D Neuroscience Data, Data Science & AI - Ophthalmology to be located at one of our offices inCambridge MA, Titusville NJ, Raritan NJ, Spring House PA, or San Diego CA (La Jolla area). Remote work arrangements may be considered on a case-by-case basis and if approved by the company.

Role Summary

We are seeking an Associate Director, R&D Neuroscience Data, Data Science & AI (DDSAI) - Ophthalmology to join our team. This leader will shape and execute innovative strategies leveraging multimodal data sources, digital health technologies, computer vision, artificial intelligence (AI), and clinical/real-world evidence (RWE) to accelerate drug discovery and development and maximize patient impact. By combining ophthalmology expertise with strong data science acumen, this role will enhance clinical trial execution and ensure that new solutions are patient-centric and ready for regulatory and payer acceptance. As an integral member of a highly matrixed team, the Associate Director will collaborate with cross-functional experts in the Neuroscience Therapeutic Area, Clinical Development, Quantitative Sciences, Regulatory Affairs, and Patient-Reported Outcomes, and forge strategic external partnerships to infuse new ideas and capabilities. This is a unique opportunity to redefine how we understand and treat eye diseases-uncovering novel digital biomarkers and endpoints, stratifying patients for more personalized care, and ultimately delivering better outcomes for people living with ophthalmic diseases.

Key Responsibilities

  • Innovative Data Analysis: Collaborate in the development and application of advanced AI/ML methods, including cutting-edge computer vision techniques applied to ophthalmic imaging data (e.g., Optical Coherence Tomography and fundus images), to uncover disease mechanisms and identify novel biomarkers.
  • Digital Endpoints & Tools: Collaborate in the development and validation of novel digital endpoints. Engage with regulatory stakeholders to ensure these innovations enhance clinical trial design, improve patient monitoring and care pathways, and meet regulatory requirements.
  • Advanced Statistical Modeling: Develop and apply sophisticated statistical models using real-world and clinical data to generate insights into disease progression, treatment outcomes, and patient stratification. Leverage longitudinal disease modeling, Bayesian methodologies, and causal inference techniques to inform decision-making.
  • Generative AI & Multimodal Integration: Apply emerging generative AI approaches to boost data analysis and knowledge discovery, integrating diverse multimodal datasets (imaging, clinical, wearable, etc.) for a more holistic understanding of ophthalmic diseases.
  • Real-World Evidence Integration: Partner with Clinical Development and Medical Affairs to integrate RWE into evidence generation strategies. Support trial optimization and regulatory submissions by incorporating insights from large-scale clinical datasets, electronic health records (EHRs), and other real-world data sources.
  • Collaboration & Leadership: Build strong cross-functional collaborations within the company and spearhead external partnerships with academic institutions, technology providers, regulators, and industry consortia.


Qualifications

  • An advanced degree (PhD, MD, or equivalent) in computational ophthalmology, neuroscience or a quantitative field such as biomedical engineering, data science, biostatistics, computational biology, or related discipline.
  • 6+ years of relevant industry or academic experience with a strong record of success in applying data science within biology/medicine, ideally influencing cross-disciplinary teams at the intersection of data science, biomedical research, and clinical development.
  • Experience in clinical development is required with experience in ophthalmology preferred.
  • Deep experience in computer vision and deep learning applied to biomedical imaging (especially ophthalmic imaging such as fundus photography and OCT). Familiarity with model validation, reproducibility, and regulatory considerations for AI tools in healthcare.
  • Experience working with large-scale, multimodal clinical datasets (including EHRs and sensor/wearable data). Proven skills in advanced statistical modeling (e.g., longitudinal analyses, Bayesian methods, causal inference) to glean meaningful insights from complex data.
  • Hands-on experience implementing digital health technologies-such as wearables, sensors, and mobile platforms-in clinical research or care settings. Understanding of how to operationalize these tools in clinical trials is a plus.
  • Proficiency in programming and data analysis tools/environments (e.g., Python, R, or comparable platforms) with a hands-on ability to develop and validate analytical workflows.
  • Excellent communication skills with the ability to translate complex data-driven insights into clear, actionable strategies for diverse stakeholders, including senior leadership, clinicians, and external partners.
  • A track record of scientific contributions demonstrated by relevant publications, conference presentations, or patents in fields such as data science, ophthalmology, or digital health.
  • Familiarity with healthcare data standards, data privacy regulations, and the pathways for regulatory qualification of novel digital endpoints or AI tools

This position will be located on-site at one of our campuses in either Spring House PA, Cambridge MA, Titusville NJ, Raritan NJ, or San Diego, CA. Remote work arrangements may be considered on a case-by-case basis and if approved by the company. Occasional travel for crossfunctional workshops, design sessions, and team meetings may be required.
Johnson & Johnson is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, age, national origin, disability, protected veteran status or other characteristics protected by federal, state or local law. We actively seek qualified candidates who are protected veterans and individuals with disabilities as defined under VEVRAA and Section 503 of the Rehabilitation Act.
Johnson & Johnson is committed to providing an interview process that is inclusive of our applicants' needs. If you are an individual with a disability and would like to request an accommodation, external applicants please contact us via https://www.jnj.com/contact-us/careers , internal employees contact AskGS to be directed to your accommodation resource.
The anticipated base pay range for this position is $137,000 to $235,750. The Company maintains highly competitive, performance-based compensation programs. Under current guidelines, this position is eligible for an annual performance bonus in accordance with the terms of the applicable plan. The annual performance bonus is a cash bonus intended to provide an incentive to achieve annual targeted results by rewarding for individual and the corporation's performance over a calendar/performance year. Bonuses are awarded at the Company's discretion on an individual basis. Employees and/or eligible dependents may be eligible to participate in the following Company sponsored employee benefit programs: medical, dental, vision, life insurance, short- and long-term disability, business accident insurance, and group legal insurance. Employees may be eligible to participate in the Company's consolidated retirement plan (pension) and savings plan (401(k)).

Employees are eligible for the following time off benefits:
Vacation - up to 120 hours per calendar year
Sick time - up to 40 hours per calendar year
Holiday pay, including Floating Holidays - up to 13 days per calendar year of Work, Personal and Family Time - up to 40 hours per calendar year
Additional information can be found through the link below.https://www.careers.jnj.com/employee-benefits

The compensation and benefits information set forth in this posting applies to candidates hired in the United States. Candidates hired outside the United States will be eligible for compensation and benefits in accordance with their local market.


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Required Skills:

Preferred Skills:

Advanced Analytics, Business Case Modeling, Consulting, Cross-Functional Collaboration, Data Privacy Standards, Data Science, Data Structures, Digital Fluency, Digital Strategy, End to End Implementation, Global Market, Negotiation, Organizing, Predictive Modeling, Process Improvements, Product Portfolio Management, Technical Credibility