Lead Data Scientist - 61282BR
Compensation: $94,330.00 - $148,460.00 /year *
Employment Type: Full-Time
Industry: Information Technology
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Req ID: 61282BR
Looking for opportunities to use cutting edge technologies analyzing petabytes of data in a world class Hadoop cluster, generating insights to guide consumers in their journey to wellness and help them achieve their health ambitions, whether its running the Inca Trail Marathon or playing tackle football with their grandkids? Aetna's Member Analytics team is focused on delivering strategically-impactful programs and tools to help members across all life stages feel the joy of achieving their best health, in their own way.
Fundamental Components included but are not limited to:
This position will play a lead role within a cross-functional team, delivering predictive analytics solutions to drive
customer engagement and next-best-action, and improve customer experience across critical journeys, e.g., onboarding, breast cancer, maternity. The candidate will lead a project team responsible for extracting and
manipulating data from multiple, large data sources, using the data to deliver predictive models and solutions, partnering with internal stakeholders to target members across channels (mobile app, web, email, social, call center, Apple), and managing day-to-day interactions with business stakeholders.
+ Lead team of 2-3 Data Scientists on the development
and delivery of predictive analytics solutions to drive behavior change
or customer experience across channels
+ Consults with business partners to understand
problems and goals, understand business value, and translate into
business opportunities to be captured through predictive analytics
+ Develops and/or uses advanced algorithms and
statistical predictive models and determines analytical approaches and
modeling techniques to evaluate scenarios and potential future outcomes
+ Demonstrates superior communication skills, and
ability to develop and participate in presentations and consultations to
business stakeholders on analytics results and solutions
+ Supports deployment of insights across multiple
channels, i.e., web, mobile app, email, social, call center, Apple watch
+ Motivates team members and probes into technical
+ Contributes Subject Matter Expertise (SME) through
interactions with team members, peers and managers to exchange complex
information related to areas of specialization
+ Mentors others, and champions 360-feedback across
Qualifications Requirements and Preferences:
We are looking for candidates who embrace the explorer mindset of asking questions, iterating quickly, being comfortable pivoting intelligently, and moving fast.
+ Background in healthcare (payer, pharmacy, PBM,
clinical), insurance, technology, or finance
+ 7-10 or more years of progressively complex related
+ Advanced in-depth specialization in mathematical
analysis methods, statistical analyses, and predictive modeling
+ Expertise in using R or Python to manipulate large
data sets and develop statistical models
+ Expertise in data management in a Hadoop environment,
including use of Hive
+ Excellent problem solving skills, critical thinking
and conceptual thinking abilities
+ Superior skills to effectively communicate technical
ideas and results to non-technical clients in written and verbal form
+ Ability to negotiate and manage interactions across
the business and project stakeholders
+ Experience regularly working collaboratively with
others to solve problem
+ Benefit Eligibility
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.
Associated topics: biomedical, dietetic, histotechnologist, immunoassay, immunohematology, injury, kinesiology, nutrition, physiology, toxicologist
* The salary listed in the header is an estimate based on salary data for similar jobs in the same area. Salary or compensation data found in the job description is accurate.
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