Senior Data Scientist I, Real World Evidence (RWE), Life Sciences R&D
Boston
- Pay
- Pay not listedSimilar roles state $118K–$193K
- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingLead design and delivery of RWE analyses for key pharma clients
Derive complex real-world endpoints from Tempus clinical and molecular data
Interpret RWE results and communicate methods and findings to varied stakeholders
Build reusable code and internal packages across collaborations
Use LLMs and agentic workflows to speed up coding, review and insight generation
From the employer’s posting
Lead the design and execute delivery of RWE analyses for key pharma clients.
Lead the derivation of complex real-world endpoints using extensive coding
Interpret results of RWE analyses to draw appropriate inferences based on study design/statistical methods
Contribute to reusable code and internal packages that can be applied across multiple collaborations.
Incorporate LLMs, agentic workflows and other AI tools into day-to-day workflows to accelerate code development, discovery, documentation, review, and insight generation.
What you’ll bring
All qualificationsCore experience
- Master’s degree and 4+ years of additional work experience
- Experience working with Pharma or drug development.
- Proven expertise in executing RWD analytical studies.
- Experience in clinical trial design (particularly Phase II-III) in the clinical development space.
- Proficient in using R and SQL, especially statistical tools and packages.
- Practical experience building, fine-tuning, or configuring LLM-based tools and agentic workflows specifically for scientific discovery.
Qualification wording
Master’s degree and 4+ years of additional work experience
Experience working with Pharma or drug development.
Proven expertise in executing RWD analytical studies.
Experience in clinical trial design (particularly Phase II-III) in the clinical development space.
Proficient in using R and SQL, especially statistical tools and packages.
Practical experience building, fine-tuning, or configuring LLM-based tools and agentic workflows specifically for scientific discovery.
Education & alternatives
Minimum Qualifications - Education: Education in epidemiology, biostatistics, data science, public health, or a related field, to the level of either:- PhD and 2+ years of additional work experience - Master’s degree and 4+ years of additional work experience
- Education: Education in epidemiology, biostatistics, data science, public health, or a related field, to the level of either:- PhD and 2+ years of additional work experience - Master’s degree and 4+ years of additional work experience - Technical and Statistical Proficiency- Expert-level proficiency with observational real-world healthcare data, including analytical experience with time-to-event methodologies (survival analysis).
Tools in this posting
- R
- SQL
- AWS
- BigQuery
- GCP
Source — Tool mentions in context
- 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., Claude Code, Copilot, Cursor) and agentic frameworks to support data analysis, code review, or scientific documentation workflows.
- Significant experience analyzing biomarker, genomic, or other high-dimensional molecular data alongside clinical datasets. - Experience with cloud platforms such as AWS and/or BigQuery and/or Google Cloud Platform (GCP). #LI-DA1
Posting record
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- Live
- First seen by us
- Sep 30, 2026 · 29 days ago
- Recorded sightings
- 60
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
- Ask the employer about the pay range before committing time to the process.
Complete your application on tempus.wd5.myworkdayjobs.com. The employer’s form will show what is required.
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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.
The Real World Evidence (RWE) group within the Life Sciences 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 Sr. Data Scientist I 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: Lead the design and execute delivery of RWE analyses for key pharma clients. You will be responsible for translating complex drug development questions and into actionable research plans that use Tempus data for 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: Build technical standards for the team, staying up-to-date on methodological advancements in real-world studies (e.g., causal inference, survival analysis) and oncology guidelines (NCCN and ongoing clinical trials). Contribute to reusable code and internal packages 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 practice. You will proactively identify gaps in current products and ensure that customer feedback is represented in development of new products.
- Oncology & RWE Domain Expertise: Grow and maintain deep expertise in oncology clinical guidelines (e.g., NCCN) and emerging RWE methodologies.
Minimum Qualifications
- Education: Education in epidemiology, biostatistics, data science, public health, or a related field, to the level of either:
- PhD and 2+ years of additional work experience
- Master’s degree and 4+ years of additional work experience
- Technical and Statistical Proficiency
- Expert-level 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., Claude Code, 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).
- Experience with code review.
- 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 building, fine-tuning, or configuring LLM-based tools and agentic workflows specifically for scientific discovery.
- Knowledge of oncology guidelines (e.g., NCCN).
- Significant experience analyzing biomarker, genomic, or other high-dimensional molecular data alongside clinical datasets.
- Experience with cloud platforms such as AWS and/or BigQuery and/or Google Cloud Platform (GCP).
#LI-DA1
USA: $120,000-$170,000
NYC/SF: $130,000-$180,000
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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