Requirements
- Proven experience as a Data Scientist with a focus on healthcare data analysis and modeling.
- 3 - 8 years of experience in two or more programming languages such as SQL, Python, Scala, Java or R, and familiarity with data manipulation and visualization libraries/tools.
- 3 - 8 years of experience in Statistical analysis, Data Modeling, Data Extraction, Data Mining, and Data Manipulation.
- Solid understanding of machine learning techniques (e.g., regression, classification, clustering) and experience applying them to healthcare data.
- Hands-on experience with healthcare data standards (e.g., HL7, FHIR), electronic health records (EHR) and other healthcare data sources.
- Excellent problem-solving and analytical skills, with the ability to communicate complex data insights in a clear and accessible manner to stakeholders with varying levels of technical expertise.
- The ability to identify key challenges, formulate data-driven solutions, and work with diverse stakeholders to implement those solutions.
- Experience in working with sensitive patient data while ensuring compliance and data security.
- A passion for using data science to drive positive change and make a meaningful difference in people's lives.
- Strong people skills, specifically in collaboration and teamwork.
- High level of curiosity, creativity, technical vision, and problem-solving capabilities; have a customer-first and learner’s mindset, and value teaching others.
- Familiarity with big data tools and platforms
Job Responsibilities
- Utilize advanced statistical and machine learning techniques to analyze healthcare data sets and extract actionable insights.
- Develop predictive models and algorithms to identify trends, patterns, and correlations in healthcare data.
- Evaluate and validate model performance using appropriate metrics and methodologies.
- Lead ongoing tracking and monitoring of performance of decision systems and statistical models.
- Develop ETL (extract, transform, load) specifications to go from raw data to research-ready datasets
- Collaborate cross-functionally with stakeholders and leadership to design and implement data-driven solutions that address complex healthcare challenges.
- Develop and drive adoption of enterprise-wide analytics to support strategic execution using prescriptive and predictive analytics with a focus on Healthcare access, Healthcare outcomes, and SDoH domains.
- Engage and enable team members to access analytics to facilitate faster data-driven decision-making wherever and whenever they need it.
- Analyze and incorporate external data sets that may augment the power of CareMessage internal data such as social determinants of health data, claims data, environmental data, outcomes data.
- Interpret complex data analyses by applying findings to contextual settings; and developing insights, reports, and presentations telling a compelling story to stakeholders to enable and influence decision-making.
- Stay updated with the latest advancements in data science, healthcare analytics, and regulatory requirements to ensure compliance and relevance.
- Job shadow other functional areas to learn from domain experts.
Within 1 Month You'll:
- Gain a foundational understanding of our product, customers and patients.
- Meet key internal stakeholders and begin to understand policies and protocols.
- Establish rapport with existing Engineers across various product teams.
- Build out basic understanding of existing data.
Within 3 Months You'll:
- Gain a strong understanding of our technical environment and identify areas for growth in our processes, systems and/or tooling for data analysis.
- Develop ETL specifications in conjunction with a Data Engineer to allow the implementation of a data pipeline to create a research-ready dataset.
- Work with a business unit to create at two or more reports to facilitate faster data-driven decision-making.
Within 6 Months You'll:
- Have a deep understanding of the product platform, our data needs and work in conjunction with management to refine the plan to meet our long term data goals.
- Utilize Data Science skills to generate a set of actionable insights for a functional area.
- Analyze and incorporate health outcomes data to augment CareMessage telemetry data to illustrate improvements in patient health by usage of the CareMessage platform.
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