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At Veracyte, the business and/or technical problem is to analyze millions of records of real-world insurance claims and EHR data to define clinical treatments and outcomes, and to develop AI/ML models for digital pathology using the world's largest database of cancer patients.

Requirements

• Proficient in SQL and R.
• 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 in summarizing and communicating findings from data, including an attention to detail when sharing findings.
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud Platform) is desirable.
• Research experience with developing AI models such as LLM, vision/time series foundation models.

Responsibilities

• Assist in analyzing 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.
• Assist in conducting statistical analysis and survival modelling for the clinical events defined from real-world data.
• Ability to visualize finding from the data and summarize them in a coherent story.
• Support data scientists in developing digital pathology AI models
• Work with bioinformatician, statistician, and medical experts in manuscripts.

Other

• PhD in Statistics, Data Science, or equivalent field.
• 3+ years of experience of data/applied scientist role or equivalent.
• Experience in working with real-world data of insurance claims and EHR records
• Ability to work effectively in a fast-paced and collaborative environment.
• Eagerness to learn new technologies and adapt to evolving requirements.