Senior Data Scientist - Statistician, Causal Inference
About the company
At Covera Health, we have proven that advanced data science can prevent serious misdiagnoses which result in poor outcomes for patients and increased costs for payers. Using our proprietary framework, we help patients recover better, faster, and more affordably. Today, we are working with some of the largest healthcare payers in the country to potentially impact millions of patient lives. We are passionate about improving healthcare for every patient.
About the role
We are looking for a talented Senior Data Scientist in Statistics to join us in our commitment to improve the quality of care for patients in every community across the nation. It is crucial that you have a Masters or PhD with a thesis and work in application of statistics methodologies, especially longitudinal data analysis and causal inference.
You will work with a growing multidisciplinary team of talented data scientists, other statisticians, engineers, and researchers to leverage unique healthcare data (in the form of MRI images, clinical reports, claims data, and beyond) to create new and improved methods for assessing and predicting the quality of care delivered by healthcare providers and determining the impact that care quality has on overall patient outcomes and cost. You will have the opportunity to work with entirely unique healthcare datasets that cover all phases of care delivery (referral, diagnosis, therapy, and outcome/follow-up) from the perspective of all key stakeholders (patients, providers, payers).
Your responsibilities will also include helping to further create, extend, and validate the statistical models that we use at Covera Health to power our analytics. You will also help to characterize, interpret, and share the results we achieve in our healthcare research studies. Your responsibilities will also include helping to shape our data analytics strategy by identifying new opportunities and helping to lead and mentor junior members of the analytics team.
You will be expected to:
• Leverage a variety of healthcare data, including healthcare provider profile data, longitudinal claims data, and proprietary diagnostic imaging exam quality assessment data, to quantify the relationship between healthcare quality and patient outcomes, costs, and care patterns
• Create, extend, and validate models and methods for causal analysis and outcome prediction
• Collaborate with data science team members and other colleagues on data analysis projects and research activities
• Communicate the results of analysis and research projects to internal and external stakeholders
• Prepare and contribute material for academic publication and participate in scientific conferences
• Lead and mentor junior members of the data science team
• Help to shape Covera Health’s data analytics strategy by identifying new opportunities
- 3+ years work experience as a Data Scientist
- PhD in statistics, biostatistics, healthcare economics, applied math, or related field
- Extensive experience with causal inference and related statistical methodologies
- Extensive experience with large and diverse datasets
- Extensive experience with Python and/or R
- Experience developing code that is leveraged by a wider team and/or contributing to a collaborative code base
- Experience designing scientific studies and quantitatively characterizing and sharing their results
- Strong communicator with excellent ability to work in a team environment
- Experience working with medical data
You will be a full-time employee with competitive salary, stock options, and great benefits. These benefits include medical, dental, and vision insurance (with premiums fully covered), FSA, pre-tax commuter benefits, flexible paid time off, and a comfortable office space filled with a variety of quality snacks and beverages. Most importantly, you’ll get to know each of us and we love to work together to find solutions. We are a smart, fun, focused, and unique team of people who are truly passionate about changing healthcare for the better!