Aetna Lead Data Scientist in Wellesley, Massachusetts
Req ID: 66314BR
The Clinical Products data science team helps supercharge CVS-Aetna s clinical programs to improve member health and lower costs. Given CVS-Aetna s size, scope, and deep set of capacities, CVS-Aetna is an unparalleled platform to make a difference in healthcare in the US and beyond. The Clinical Products team has three main goals. First, CVS-Aetna is launching a series of clinical programs that use the resources of the combined CVS-Aetna, and our team delivers the advanced analytics to support those initiatives. Second, the team develops data-driven clinical recommendations that are delivered to members, their providers, and their caregivers. Finally, we build condition-specific models that help other parts of the company (e.g. pricing) better predict member care journeys.
About the position. A Lead Data Scientist will join the newly formed Clinical Products team and will be responsible for, end to end, projects that support one or more of the team s three objectives. A Lead Data Scientist will lead a team that develops predictive models, works with clinical experts (e.g. doctors) to translate their subject matter expertise into machine learning models, sources data, and presents to technical and non-technical stakeholders. A Lead Data Scientist will also manage and be responsible for using the results of AB testing to improve the performance of the team s statistical modeling and targeting. A Lead Data Scientist will also mentor team members.
Culturally, because we are a new team, we are looking for candidates who embrace the “explorer mindset of asking questions, iterating quickly, being comfortable pivoting intelligently, and moving fast.
Fundamental Components included but are not limited to:
Develops and/or uses algorithms and statistical predictive models, including advanced models.
Brings clinical insights to inform predictive models: is skilled at reading academic clinically oriented literature and collaborating with clinical subject matter experts to inform predictive models.
Performs analyses of structured and unstructured data to solve multiple and complex business problems. Utilizing advanced statistical techniques and mathematical analyses and specialized expertise in the Aetna and/or healthcare.
Applies analytical rigor and statistical methods to analyze large amounts of data, using advanced statistical techniques.
Manages large and complex analytical projects from data exploration, model building, performance evaluation and testing
Behaves as mentor to junior team members to provide technical advice
Collaborates with business partners to develop technical /business approaches and new or enhanced technical tools
Interacts with internal and external peers and management to share highly complex information related to areas of expertise and/or to gain acceptance of new or enhanced technology / business solutions
Qualifications Requirements and Preferences:
7-10 or more years of progressively complex related experience
Demonstrates proficiency in all areas of mathematical analysis methods, machine learning, statistical analyses, and predictive modeling and advanced in-depth specialization in some areas
Solid understanding of health care industry, products, and systems
Deep knowledge of advanced analytics tools and languages to analyze large data sets from multiple data sources
Strong skills to effectively communicate and negotiate across the business and in the external health care environment Demonstrates strong ability to communicate technical concepts and implications to business partners
Strong organizational, management and leadership skills
Excellent analytical and problem solving skills
Clinically oriented background or professional experience is a plus.
Benefit eligibility may vary by position. Click here to review the benefits associated with this position.
Job Function: Data & Analytics
Aetna is an Equal Opportunity/Affirmative Action employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or protected Veterans status.