Drug companies, device manufacturers, hospitals, providers–they are all connected by a web of complex financial relationships. These relationships often benefit patients and the public by driving new technological innovations–but not always. At Conflixis, our goal is to find those financial relationships that lead to higher costs or worse outcomes for patients. We use a variety of massive data sets, existing research and expertise to drive machine learning models that surface these risky relationships. We sell this information to the people who will use it to make our system better.

We are seeking an experienced data scientist to join our team, with expertise in claims and provider data and experience with cloud platforms such as Azure and GCP.

Key Responsibilities:

• Lead the identification, analysis, and integration of healthcare data sources (claims, provider, financial, etc.) to generate insights that optimize patient care and healthcare operations.
• Architect and drive the development of advanced machine learning models and predictive analytics tools to assess risk, detect fraud, and identify conflicts of interest within the healthcare ecosystem.
• Oversee data cleaning, transformation, and large-scale integration of complex healthcare datasets, utilizing tools such as BigQuery, Snowflake, or equivalent cloud data solutions.
• Collaborate closely with data scientists and engineers to design, implement, and refine algorithms that address real-world healthcare problems, ensuring compliance with industry standards and regulatory requirements (HIPAA, SOC).
• Provide expert-level analysis on claims data trends and provider behavior, delivering high-impact presentations and reports to stakeholders at all levels, including C-suite and external clients.
• Manage the deployment and scaling of predictive models using cloud platforms like Azure, GCP, or AWS to ensure data pipelines and analytics solutions are robust and secure.
• Implement best practices for data governance, ensuring the integrity, security, and compliance of all data operations, with particular focus on healthcare regulations and privacy requirements.

Required Qualifications:

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field. Advanced degrees preferred.
• 5+ years of experience in data analytics with a specific focus on healthcare claims, provider data, and healthcare reimbursement systems.
• Demonstrated expertise in healthcare data analytics, including deep familiarity with claims processing, provider networks, and regulatory frameworks.
• Advanced proficiency in Python, R, and SQL for large-scale data analysis, model building, and statistical computations.
• Strong experience with machine learning techniques (supervised, unsupervised, NLP) and demonstrated success in developing and deploying predictive models in a healthcare context.
• Hands-on experience with cloud platforms (Azure, GCP, AWS) for data processing, analytics, and machine learning model deployment.
• Proven ability to manage complex data projects, including the ability to lead cross-functional teams, set project goals, and drive outcomes.

Preferred Qualifications:

• Experience working with AI models in healthcare risk management.
• Knowledge of health economics, outcomes research (HEOR), or public health data.

What We Offer:

• Competitive salary and benefits package.
• Opportunities for career development and professional growth.
• A collaborative, fast-paced environment focused on innovation in healthcare analytics.
• Opportunity for equity in the company

**Candidates must be authorized to work in the United States