Data Scientist, Privacy

📋 Description

• • Join Datavant, a leading data collaboration platform dedicated to making health data secure, accessible, and actionable. We are at the forefront of transforming healthcare by providing critical data solutions to a diverse range of organizations, including providers, health plans, researchers, and life sciences companies. Our mission extends from facilitating individual patient record access to powering the AI revolution in healthcare, fundamentally changing how data is connected and utilized to improve health outcomes.
• • As a Data Scientist on the Privacy Science team within our Privacy Hub, you will be instrumental in safeguarding patient privacy in an increasingly data-driven world. This role offers a unique blend of working with real-world data and engaging in cutting-edge research to maintain our industry leadership in privacy-preserving technologies.
• • You will actively participate in stimulating discussions surrounding re-identification risk, contributing to the development of robust privacy methodologies. We are committed to supporting your professional growth, providing opportunities to develop and consolidate your data analysis and coding skills, ultimately enabling you to become proficient in analyzing large, complex health-related datasets.
• • Your core responsibilities will involve critically analyzing vast health datasets. This will require the application of both standard and bespoke software libraries to extract meaningful insights and identify potential privacy vulnerabilities.
• • You will be expected to communicate your findings and progress effectively. This includes engaging in discussions with internal teams and external stakeholders, ensuring transparency and collaborative problem-solving.
• • A key output of your work will be the production of high-quality reports that clearly and concisely summarize your analytical findings. These reports will be crucial for informing strategic decisions and demonstrating compliance with privacy standards.
• • You will contribute directly to our ongoing research activities. This involves exploring both novel and established sources of re-identification risk, pushing the boundaries of privacy science and developing innovative solutions.
• • This role demands a meticulous attention to detail, especially in the creation of comprehensive and well-presented reports that accurately reflect your analytical work.
• • You will leverage your understanding of statistical concepts, including probability distributions, bias, error, and power, as well as sampling and resampling methods, to inform your analysis and conclusions.
• • A crucial aspect of this role is the ability to understand real-world data within its specific context, rather than treating it as abstract information. This contextual understanding is vital for accurate analysis and meaningful insights.
• • You will utilize programmable data analysis software such as R or Python. While familiarity is beneficial, a strong desire to develop deep expertise in these languages is essential for success in this role.
• • The application of scientific methods to practical problems is central to this position. You will employ experimental design, exploratory data analysis, and hypothesis testing to arrive at robust and defensible conclusions.
• • Strong time management skills are paramount. You will need to demonstrate a proven ability to prioritize tasks effectively and meet tight deadlines in a fast-paced environment.
• • Initiative and independence are highly valued. You will be encouraged to independently explore and research novel topics and concepts as they arise, contributing to the expansion of the Privacy Hub's collective knowledge base.
• • A fundamental appreciation for the importance of effective data privacy and security methods is required. You should also possess an awareness of relevant legislation and regulatory frameworks governing health data.
• • Familiarity with cloud-based storage and computing facilities, particularly Amazon Web Services (AWS), will be advantageous for managing and processing large datasets.
• • This role is ideal for a proactive and analytical individual passionate about the intersection of data science and healthcare privacy, eager to make a tangible impact on patient data protection and the advancement of healthcare innovation.