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Data Scientist III – Temporary

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Remote from
USA
Salary
USD 63–72 / hour
Employment
Contract
Experience
Open level
Published
Apply before
4 Nov 2026
Listing views
18
Application actions
2
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AI Summary

The role, at a glance.

Veracyte is seeking a temporary contract Data Scientist III to analyze large-scale real-world insurance claims and EHR data for cancer-care research. The role combines ETL, SQL, R-based data preparation, statistical analysis, survival modeling, visualization, and clinical storytelling. The successful candidate will collaborate with bioinformaticians, statisticians, and medical experts while supporting digital pathology AI initiatives and scientific manuscripts. Strong experience with oncology-related real-world data, coding systems such as CPT/NDC/ICD, cloud platforms, and peer-reviewed research is highly relevant.

Role DNA

A quick view of the complexity, pace, ownership and collaboration implied by the job description.

Job Complexity

5/5
EasyHard

Pace & Pressure

4/5
RelaxedFast-paced

Autonomy Level

4/5
GuidedFull ownership

Communication Load

5/5
IndependentCollaborative
AI insightThis is a senior applied data-science role requiring advanced statistical modeling, complex healthcare data interpretation, and rigorous research communication. The candidate must independently translate ambiguous clinical and business questions into reproducible analyses while collaborating across technical and medical disciplines.

Salary analysis

Estimated compensation compared with the broader US market for similar roles.

Estimated job medianMarket rate
$68
US market range$55–$85
AI insightThe disclosed contractor pay range is $63 to $72 USD per hour, with a midpoint of $67.50 per hour. For a US-based senior healthcare/clinical data scientist contractor with SQL, R, real-world evidence, and survival-modeling expertise, an estimated market range is approximately $55 to $85 USD per hour; actual pay may vary by location, oncology domain expertise, and contract terms.

Core skills

Skills and capabilities most closely associated with this opportunity.

Sample interview questions
How would you define cancer progression from insurance claims and EHR data?

I would first align with clinical experts on a transparent operational definition, then combine diagnosis, procedure, medication, pathology, and free-text signals using CPT, ICD, and NDC codes. I would validate timing rules and outcome labels against chart-reviewed or otherwise trusted subsets, document assumptions, and assess sensitivity to alternative definitions.

Describe your approach to a survival analysis with observational real-world data.

I would define the index date, eligibility criteria, follow-up window, outcome, censoring rules, and clinically meaningful covariates before modeling. I would inspect missingness and proportional-hazards assumptions, use Kaplan-Meier curves and multivariable Cox models where appropriate, and consider confounding controls such as propensity methods or stratification. I would communicate both effect estimates and limitations arising from residual confounding or data capture gaps.

How do you build reliable ETL pipelines for large healthcare datasets?

I begin with a documented source-to-target mapping and create modular SQL transformations with data-quality checks for completeness, duplicates, coding validity, and temporal consistency. I version code, make transformations reproducible, and use cloud storage and compute efficiently for large tables. I also maintain clear lineage so downstream analysts can understand how each analytic variable was created.

How would you explain a complex AI or statistical model to clinicians and nontechnical stakeholders?

I would start with the clinical question and decision context rather than the model mechanics. I would use plain-language visuals, describe inputs and outputs, show performance and uncertainty, and explain important limitations such as population applicability and potential bias. Technical appendices can provide the methodological depth needed for scientific review.

Tell us about how you would prepare an analysis for a peer-reviewed manuscript.

I would develop a prespecified analysis plan, ensure cohort construction and statistical code are reproducible, and generate publication-quality tables and figures. I would clearly report data sources, eligibility criteria, variable definitions, model assumptions, effect estimates, and limitations. Throughout drafting, I would work closely with clinical and statistical collaborators to ensure the conclusions are accurate and appropriately supported.

This analysis is generated from the job description. Salary estimates, role characteristics and sample answers are guidance, not employer-provided facts.
Opportunity details

About this role.

At Veracyte, we offer exciting career opportunities for those interested in joining a pioneering team that is committed to transforming cancer care for patients across the globe. Working at Veracyte enables our employees to not only make a meaningful impact on the lives of patients, but to also learn and grow within a purpose driven environment. This is what we call the Veracyte way – it’s about how we work together, guided by our values, to give clinicians the insights they need to help patients make life-changing decisions.

Our Values:

  • We Seek A Better Way: We pursue bold ideas, embrace complexity, and keep pushing forward.
  • We Make It Happen: We act with urgency, deliver with excellence, and always find a way.
  • We Are Stronger Together: We engage with empathy, align around what’s best for Veracyte, and celebrate as one team.
  • We Care Deeply: We show up with integrity, kindness, and respect for one another.

The Position:

We are seeking a talented and experienced data scientist III (contractor) to join our Data Analysis Team (DAT), as part of the R&D group for Veracyte Inc. This position offers a unique opportunity to work with experienced professionals to carry out AI/ML modelling and analysis of the world’s largest database of cancer patients, encompassing multi-platform digital pathology, genomic and clinical outcome data.

The primary objective of this role is to analyze millions of records of real-world insurance claims and EHR data to define clinical treatments and outcomes. The successful candidate needs to be proficient in state-of-art data extraction, transformation and loading (ETL), and statistical analysis to convert data into meaningful insights and stories. The candidate will also need to communicate and understand business needs, identify relevant data, process and analyze data accordingly. Experience of academic writing and prepare data/figures for manuscript are necessary for success in this position. The candidate should also be able to design graphics to explain AI models with known clinical or genomic features. Strong track record of publishing in both clinical and technical peer-review journals or conferences is highly desired. The ideal candidate is passionate about data, eager to learn independently, and possesses strong analytical, problem-solving, and storytelling skills.

KEY RESPONSIBILITIES: 

  • Analyze real-world data to identify patterns for various clinical and business cases, including treatment patterns and management costs.
  • Participate in Identifying key clinical events, such as cancer progression and treatments, using CPT, NDC, ICD codes, and structured database free text.
  • Conduct statistical analysis and survival modeling for clinical events defined from real-world data.
  • Ability to visualize findings from the data and summarize them in a coherent story.
  • Support data scientists in developing digital pathology AI models
  • Partner closely with bioinformaticians, statisticians, and medical experts in manuscripts.

Who You Are:

REQUIRED EXPERIENCE:  

  • PhD in Statistics, Data Science, or equivalent field. Or Master of 4+ years of relevant post-graduate experience
  • Experience in working with real-world data of insurance claims and EHR records
  • Expert in SQL and R or equivalent
  • Strong skills with data clean-up, manipulation and visualization using tidyverse, ggplot in R or equivalent. 
  • Proficient in statistical analysis, especially in survival modelling and hypothesis testing (i.e., multivariate regression modelling with interaction effects).
  • Experience working in cloud computing environments (AWS preferred).  
  • Demonstrated proficiency and attention to detail in summarizing and communicating findings from data.
  • Ability to work effectively in a fast-paced and collaborative environment. 
  • Eagerness to learn new technologies and adapt to evolving requirements.  

RELEVANT EXPERIENCE (preferred but not required):  

  • Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) is desirable. 
  • Knowledge of basic bioinformatics, genomics, and cancer biology 
  • Past research experience in urological oncology, bioinformatics, digital pathology, or relevant fields 
  • Research experience with developing AI models such as LLM, vision/time series foundation models.

LOCATION:

  • This is a remote friendly position.

#LI-Remote

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to years of experience, skillset, geographic location, industry, education, etc. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Pay range

$63—$72 USD

The final salary offered to a successful candidate will be dependent on several factors that may include but are not limited to years of experience, skillset, geographic location, industry, education, etc. Base pay is one part of the Total Package that is provided to compensate and recognize employees for their work, and this role may be eligible for additional discretionary bonuses/incentives, and restricted stock units.

Pay to be determined by local market and candidate experience

$63—$72 USD

What We Can Offer You

Veracyte is a growing company that offers significant career opportunities if you are curious, driven, patient-oriented and aspire to help us build a great company. We offer competitive compensation and benefits, and are committed to fostering an inclusive workforce, where diverse backgrounds are represented, engaged, and empowered to drive innovative ideas and decisions. We are thrilled to be recognized as a 2024 Certified™ Great Place to Work® in both the US and Israel – a testament to our dynamic, inclusive, and inspiring workplace where passion meets purpose.

About Veracyte

Veracyte (Nasdaq: VCYT) is a global diagnostics company whose vision is to transform cancer care for patients all over the world. We empower clinicians with the high-value insights they need to guide and assure patients at pivotal moments in the race to diagnose and treat cancer. Our Veracyte Diagnostics Platform delivers high-performing cancer tests that are fueled by broad genomic and clinical data, deep bioinformatic and AI capabilities, and a powerful evidence-generation engine, which ultimately drives durable reimbursement and guideline inclusion for our tests, along with new insights to support continued innovation and pipeline development. For more information, please visit www.veracyte.com or follow us on LinkedIn or X (Twitter).

Veracyte, Inc. is an Equal Opportunity Employer and will consider all qualified applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status or disability status. Veracyte participates in E-Verify in the United States. View our CCPA Disclosure Notice

If you receive any suspicious alerts or communications through LinkedIn or other online job sites for any position at Veracyte, please exercise caution and promptly report any concerns to careers@veracyte.com

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This job listing has been manually reviewed by the Jobicy Trust & Safety Team for compliance with our posting guidelines, including verification of the company's legitimacy, accuracy of job details, clarity of remote work policy, and absence of misleading or fraudulent content.

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