Data Scientist

Job Description:

Role will support 5 business segments); these business segments drive $330m in marketing generated revenue, $40m in HSA contributions, $240M in medical cost savings, 1k MQLs.
Role will support 25 products across B2B & B2C.
The role will require a highly analytical and strategic Principal Data Scientist to drive data driven decision making and optimize marketing performance.
This role will leverage advanced analytics, machine learning and statistical modeling to uncover customer insights, enhance segmentation and predict key behaviors to drive engagement and conversion.
The role will collaborate closely with marketing, product and data engineering to ensure data accuracy, design impactful experiments and develop models that inform targeting, personalization and campaign optimization.
This role will be a key driver in future proofing our data & analytics environment as marketing initiatives expand.
Responsible for being the SME on marketing data, data pipeline development & optimization, partner with stakeholders to ensure data requirements are aligned to business priorities, maintain documentation for data processes, verifies the accuracy of the data, maintains master inventory of OH data challenges/gaps, ensure availability of enriched data sets for analytics.

Team: Position sits within the Marketing Performance Analytics & Insights Team within Optum Health. There are 9 full time on shore FTEs and 3 off shore FTEs. Part of the team (9 FTEs) are responsible for performing data analysis and mining insights to be used in marketing optimization. The other part of this team is focused on data science work this is where this position will sit. There are currently three other onshore data scientists on the team.

Responsibilities:

Create predictive models & consumer segmentation models using demographic, psychographic, econometric, and statistical data to enable personalized marketing. We have some existing models that need to be moved into a new environment and updated with a new 3rd party data source.
Collaborate with marketing stakeholders to optimize campaigns, apply customer segmentation and drive personalization strategies
Undertake rigorous and meticulous data analysis to extract and distill key population insights that will be consumed by functions such as marketing, product and client relations.
Ability to work with imperfect data. Navigate and analyze complex, incomplete and sometimes unreliable data sources, applying statistical and rule- based approaches to clean and validate data.
Enable analytic use cases by ensuring the availability of enriched data sets for campaign performance measurement, self serve analytics, audience segmentation and predictive modeling.
Investigate discrepancies in marketing datasets, troubleshoot anomalies, and collaborate with data engineers to improve data reliability and accessibility
Identify trends in member behavior and engagement.

Ideal Background: Problem Solving Mindset: excited by the opportunity to work in a complex, messy data environment, solving ambiguous problems and translating analytics into actionable strategies. Not taking no for an answer, and instead willing to find compromise or drive towards uncovering a solution when no one else will. Results driven mindset in a constantly changing environment.

Skills:

Data pipeline development
Familiar with cloud services and working in data bricks
Experience with programming language and proficiency data pipeline development
Knowledge of creating and maintaining data models tailored for marketing analytic use cases.
Proficiency in Python or R. SQL database querying experience and data manipulation/preparation.
Knowledge of ML frameworks & algorithms and implementation.
Familiarity with data visualization tools.
Ability to work in data bricks and experience at building ML models is a must

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.