Lead Data Scientist - Patient Safety
Lead Data Scientist - Patient Safety
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$ 142140 - 284280
1 Vacancy
Job Description
At CVS Health were building a world of health around every consumer and surrounding ourselves with dedicated colleagues who are passionate about transforming health care.
As the nations leading health solutions company we reach millions of Americans through our local presence digital channels and more than 300000 purposedriven colleagues caring for people where when and how they choose in a way that is uniquely more connected more convenient and more compassionate. And we do it all with heart each and every day.
Position overview
The Retail Pharmacy Analytics team maintains industryleading analytical solutions to enable a roadmap that drives the technology development & innovation while delivering highquality and highvalue solutions.
This position will be reporting to the Principle Data Scientist Patient Safety and Pharmacy Operations Analytics. As a Lead Data Scientist youll use your Data Science and ML expertise to drive our AI innovation to revolutionize the way CVS Pharmacy fills prescriptions.
As part of the patient safety team you will work on projects which apply supervised and unsupervised machine learning approaches to identify potentially fraudulent or forged prescriptions which power real time alerts sent to all 9700 pharmacy locations to prevent these prescriptions from being filled.
In this role you will be called on to work cross functionally with a range of technical and nontechnical partners. Building partnerships with multiple stakeholders translating their business needs into problems which can be solved using analytics statistics and machine learning. Additionally you will work closely with IT partners to bring these models to production at scale across the entire footprint of CVS retail pharmacies across the country.
Responsibilities include
- Lead initiatives to improve patient safety and mitigate risk of potential fraud and forgery leveraging AI/ ML techniques
- Develop analytics solutions that deploy advanced machine learning and artificial intelligence methods including supervised classification unsupervised clustering or anomaly detection graph based approaches all focused on detecting potentially fraudulent or forged prescriptions
- Conduct or coordinate appropriate testing of analytic solutions including machine learning and artificial intelligence to ensure results are consistent with business requirements
- Develop and present meaningful and insightsdriven materials on analytical results with recommendations and go forward planning to guide a variety of audiences including internal stakeholders and senior leadership
- Develop and mentor data scientists contribute to their learning and training agenda knowledge sharing and provide input on technology stack
Required Qualifications:
- 7 years of experience with development of advanced machine learning solutions
- 7 years experience with the Software Development Lifecycle (SDLC) and agile development including giving business requirements focused on data and analytics
- Experience working on Big Data and ML technologies Azure ML Hadoop Databricks R Python SQL Teradata
- Experience building production ready NLP and/or machine learning solutions and maintaining them in production
- Methodical detail oriented with experience diving deep and asking the right questions
- Ability to engage with senior business stakeholders execute level communication and influencing skills
Preferred Qualifications
- PhD or Masters degree
- AI/ML publication in a peerreviewed journal
- Demonstrates proficiency in all areas of mathematical analysis methods machine learning statistical analyses and predictive modeling and advanced indepth specialization in some areas especially in natural language processing
- Familiarity with cloud computing services (AWS GCP or Azure)
- Solid understanding of health care industry products and system
- Demonstrates a strong ability to communicate technical concepts and implications to business partners
- Prior experience implementing supervised and unsupervised approaches to address rare and anomalous events like fraud and forgery
- Prior experience utilizing graph data structures and related AI/ML approaches like GNN GCN GAT to create supervised and unsupervised graph representations of complex systems
Education
- Bachelors Degree required
- Advanced degree majoring in Statistics Computer Science Mathematics or related STEM field a plus
- Largescale deep learning model training
Pay Range
The typical pay range for this role is:
$142140.00 $284280.00
This pay range represents the base hourly rate or base annual fulltime salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience education geography and other relevant factors. This position is eligible for a CVS Health bonus commission or shortterm incentive program in addition to the base pay range listed above. This position also includes an award target in the companys equity award program.
Our people fuel our future. Our teams reflect the customers patients members and communities we serve and we are committed to fostering a workplace where every colleague feels valued and that they belong.
Great benefits for great people
We take pride in our comprehensive and competitive mix of pay and benefits investing in the physical emotional and financial wellness of our colleagues and their families to help them be the healthiest they can be. In addition to our competitive wages our great benefits include:
Affordable medical plan options a 401(k) plan (including matching company contributions) and an employee stock purchase plan.
Nocost programs for all colleagues including wellness screenings tobacco cessation and weight management programs confidential counseling and financial coaching.
Benefit solutions that address the different needs and preferences of our colleagues including paid time off flexible work schedules family leave dependent care resources colleague assistance programs tuition assistance retiree medical access and many other benefits depending on eligibility.
For more information visit anticipate the application window for this opening will close on: 04/30/2025 Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal state and local laws.
Employment Type
Full-Time
