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 a Data Analyst to join our team, with expertise in claims and provider data and experience with cloud platforms such as Azure and GCP.
Key Responsibilities:
- Collaborate with cross-functional teams to identify and utilize healthcare data sources, particularly claims data and provider data, to generate actionable insights.
- Assist in developing machine learning models and analytics tools to analyze healthcare data, predict outcomes, and optimize patient care and healthcare operations.
- Conduct advanced data cleaning, transformation, and integration of complex datasets, including healthcare claims and provider data, using tools like Bigquery or Snowflake.
- Help build predictive models and risk scoring algorithms for identifying conflicts of interest, fraud detection, and compliance monitoring.
- Leverage cloud technologies such as Elastic Cloud, Azure and GCP for data processing and model deployment.
- Provide expert analysis on claims data trends and provider behavior, presenting findings to both technical and non-technical stakeholders.
- Ensure data governance and compliance with healthcare industry regulations (HIPAA, SOC).
Required Qualifications:
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
- 2+ years of experience in data science, with a specific focus on claims data and provider data in the healthcare or insurance industry.
- Strong expertise in healthcare claims and provider data analytics, including working knowledge of healthcare reimbursement systems and claims processing.
- Proficiency in Python, R and SQL
- Familiarity with machine learning techniques, including supervised and unsupervised learning.
- Experience with Azure and Google Cloud Platform (GCP) for data processing, model training, and deployment.