Senior Data Scientist, Causal Inference
New York, NY
Full Time Senior-level / Expert USD 175K - 200K
Covera Health
Learn about the impact prevalence of radiology misdiagnosis and how Covera Health radiology programs are improving quality radiology for all.About the company
At Covera, we're committed to ensuring high-quality healthcare is more than just a promise. That's why we're leading the way in the emerging science of quality, and connecting providers and payers in their shared quest to improve patient outcomes and care quality. By tackling this challenge, we have the ability to impact millions of lives by raising the standard of care nationwide.
Our initial focus is radiology, where an early and accurate diagnosis has a profound impact on the rest of a patient's care journey. Through our work, which uses clinically-validated science-based tools, we're helping doctors enhance their care, ensuring patients get the right diagnosis, and enabling the healthcare system to support quality improvement at scale.
Through our clinical intelligence platform, we have launched programs that help people access the most effective care and provide doctors with AI-powered quality insights and tools to enhance their care. Today, Covera is partnered with leading employers, payers and healthcare organizations across the US, including Walmart and Microsoft. And, with a pipeline representing over 25% of insured Americans, we are in the early stages of improving care quality for all patients across the globe.
In November 2023, Covera secured up to $50 million in a Series C extension led by Insight Partners. This capital fuels our mission to partner with healthcare providers, payers and employers to improve diagnostic care for patients everywhere.
About the role
In this role, you will be expected to:
- Process and Analyze Healthcare Data: Work with various types of healthcare data, including longitudinal medical claims data, to quantify the relationships between healthcare quality and patient outcomes, such as cost, clinical outcomes, and care patterns.
- Conduct Statistical Analysis and Causal Inference Modeling: Conduct statistical modeling of claims data using methods like Propensity Score Matching, Propensity Score Weighting, and Difference-In-Differences. Develop, maintain, extend, and validate models and methods to quantify program savings and ROI.
- Provide Technical and Thought Leadership: Serve as an in-house expert on causal inference techniques, lead study design efforts, propose and develop Statistical Analysis Plans (SAPs), and ensure methodological rigor across projects.
- Maintain and Extend Data and Modeling Pipelines: Develop, run, and enhance our data engineering and modeling pipelines to create modeling datasets, run statistical models, and produce quarterly business performance reports.
- Improve and Troubleshoot Codebase: Review and optimize the team’s data pipelines and statistical code to enhance runtime and memory efficiency, ensure reproducibility, and support automation and scalability. Troubleshoot technical issues as they arise, working with the engineering team as needed for support.
- Conduct Ad-Hoc Analyses: Conduct ad-hoc analyses (e.g. of claims data) as business needs arise in a fast-paced environment to uncover business and clinical insights and support Covera’s strategy and decision-making.
- Prepare and Communicate Insights: Develop clear, compelling documentation and presentations for client meetings and key deliverables. Effectively communicate analytical results to both internal and external stakeholders and co-lead methodological discussions with clients.
- Collaborate: Work closely with data science team members and cross-functional colleagues across Covera on analysis requests, projects, and research initiatives.
- Publish: Author and contribute to academic publications and white papers. Serve as an ambassador for Covera’s methodologies and value proposition within the research and healthcare communities.
Your Profile:
- Educational Background: Ph.D. or M.S. in Statistics, Economics, Biostatistics, Applied Mathematics, Epidemiology, Computer Science, or a related field.
- Experience: At least 2 years of experience for PhD degree holders or 5 years for M.S. degree holders with a strong track record of applying statistical and causal inference methods to real-world healthcare data.
- Statistical and Causal Inference Expertise:
- Strong foundation in statistical modeling, including Generalized Linear Models, Mixed Models, and longitudinal data analysis.
- Expertise in study design and causal inference methodologies such as Propensity Score Matching, Propensity Score Weighting, Difference-In-Differences, and Regression Discontinuity Design.
- Coding Skills:
- Strong foundation in coding best practices, with expertise in R, Spark (specifically sparklyr), SQL, and Python for data science. Exceptional skills in R and sparklyr are required.
- Experience developing scalable code for use by a wider team and contributing to a collaborative codebase.
- Proven ability to troubleshoot code, technical issues, and optimize data pipelines effectively.
- Healthcare Data Expertise:
- Strong understanding of, and experience working with, real-world medical and claims data, including familiarity with ICD codes, CPT codes, CMS-HCC models, and comorbidity coding.
- Experience interpreting and working with medical coding standards to extract meaningful insights from healthcare datasets.
- Communication and Collaboration:
- Excellent communication skills, with a proven ability to explain complex methodologies to non-technical stakeholders.
- Enthusiasm for working in a collaborative, cross-functional team environment, paired with a proactive, problem-solving mindset.
- Industry Experience: Preferred experience working with payor organizations, healthcare consulting, and/or fast-paced, client-facing environments.
Benefits
You will be a full-time employee with a competitive salary, stock options, and great benefits. These benefits include medical, dental, and vision insurance, HRA, 401k, pre-tax commuter benefits, flexible paid time off, and a comfortable office space filled with various 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 talented, fun, focused, and unique team of people who are truly passionate about changing healthcare for the better!
The minimum and maximum salary for this position ranges from $175,000 to $200,000, in addition to a discretionary bonus and comprehensive benefits package. Final salary will be based on a number of factors including but not limited to, a candidate’s qualifications, skills, competencies, experience, expertise and location.
At Covera Health, we strive to build diverse teams that reflect the people we want to empower through our technology. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, or Veteran status. Equal Opportunity is the Law, and Covera Health is proud to be an equal-opportunity workplace and affirmative action employer. If you have a specific need that requires accommodation, please let a member of the People Team know.
Tags: Biostatistics Causal inference Computer Science Consulting Data analysis Data pipelines Economics Engineering Mathematics PhD Pipelines Python R Research Spark SQL Statistical modeling Statistics
Perks/benefits: Competitive pay Equity / stock options Flex hours Flex vacation Health care Insurance Salary bonus Snacks / Drinks
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