Data Scientist, Privacy
Datavant
Job Overview
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Job Description
Data Scientist, Privacy at Datavant
Datavant is the data collaboration platform trusted for healthcare. Guided by our mission to make the world’s health data secure, accessible and actionable, we provide critical data solutions for organizations across the healthcare ecosystem - including providers, health plans, researchers, and life sciences companies. From fulfilling a single patient’s request for their medical records to powering the AI revolution in healthcare, Datavanters are building the future of how data is connected and used to improve health.
By joining Datavant today, you’re stepping onto a driven and highly collaborative team that is passionate about creating transformative change in healthcare.
The Role
As part of the Privacy Science team within Privacy Hub, you will play a crucial role in ensuring that privacy of patients is safeguarded in the modern world of data sharing. As well as working on real data, you will be involved in exciting research to keep us as industry leaders in this area, and stimulating discussions on re-identification risk. You will be supported in developing/consolidating data analysis and coding skills to become proficient in the analysis of large health-related datasets.
Responsibilities
- Critically analyze large health datasets using standard and bespoke software libraries
- Discuss your findings and progress with internal and external stakeholders
- Produce high quality reports which summarise your findings
- Contribute to research activities as we explore novel and established sources of re-identification risk
What You Will Bring To The Table
- Excellent communication skills. Meticulous attention to detail in the production of comprehensive, well-presented reports
- A good understanding of statistical probability distributions, bias, error and power as well as sampling and resampling methods
- Seeks to understand real-world data in context rather than consider it in abstraction.
- Familiarity or proficiency with programmable data analysis software R or Python, and the desire to develop expertise in its language
- Application of scientific methods to practical problems through experimental design, exploratory data analysis and hypothesis testing to reach robust conclusions
- Strong time management skills and demonstrable experience of prioritising work to meet tight deadlines
- Initiative and ability to independently explore and research novel topics and concepts as they arise, to expand Privacy Hub’s knowledge base
- An appreciation of the need for effective methods in data privacy and security, and an awareness of the relevant legislation
- Familiarity with Amazon Web Services cloud-based storage and computing facilities
Bonus Points
- Experience creating documents using LATEX
- Detailed knowledge of one or more types of health information, e.g., genomics, disease, health images
- Experience working with or supporting public sector organizations, such as federal agencies (e.g., CMS, NIH, VA, CDC), state health departments, or public health research partners. Familiarity with government data environments, procurement processes, or privacy frameworks in regulated settings is highly valued.
Key skills/competency
- Data Privacy
- Statistical Analysis
- R & Python
- Healthcare Data
- Re-identification Risk
- Experimental Design
- AWS
- Scientific Research
- Report Generation
- Time Management
How to Get Hired at Datavant
- Research Datavant's culture: Study their mission, values, recent news, and employee testimonials on LinkedIn and Glassdoor.
- Tailor your resume: Customize your resume to highlight experience in data privacy, statistical analysis, and healthcare data, using keywords from the Datavant job description.
- Showcase privacy science expertise: Prepare to discuss your understanding of re-identification risk, differential privacy, and relevant legislation in healthcare data.
- Demonstrate technical proficiency: Be ready to showcase your skills in R or Python for data analysis, experimental design, and hypothesis testing.
- Highlight communication and detail: Practice presenting complex findings clearly and demonstrate meticulous attention to detail in previous project examples.
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