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Senior Data Scientist – Specialty Operation Optimization
| Company | CVS Health |
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| Location | New York, NY, USA |
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| Salary | $111240 – $222480 |
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| Type | Full-Time |
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| Degrees | Bachelor’s, Master’s |
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| Experience Level | Senior |
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Requirements
- Bachelor’s degree or equivalent work experience in Mathematics, Statistics, Operations Research/Industrial Engineering, Computer Science, Business Analytics, Economics, Physics, Engineering, or related discipline. Master’s degree is preferred
- 3+ years of experience in descriptive and predictive analytics including gathering requirements to meet data and technology pre-requisites
- Strategic mindset and experience leading highly technical initiatives focused on deploying data and analytics solutions in healthcare
- Ability to engage with stakeholders, communicate insights and promote adoption of analytics insights
- Deep expertise with data modeling/analytics in SQL and Python
- Highly motivated to work in a fast-paced environment and enable sustainable impact in CVS Specialty Pharmacy
Responsibilities
- Utilize analytics expertise to collaborate with senior leaders in identifying new use cases that align with ambitious goals in CVS Specialty Pharmacy
- Gather business requirements from multiple stakeholders and lead the analysis of extensive data to develop strategies and tactics for solving complex problems and optimizing tradeoffs
- Lead initiatives focused on improve operation efficiency analytics, as well as growth analytics, employing both descriptive, predictive and optimization techniques
- Guide the technical approach, leverage large datasets, and build scalable and deployment ready models (ML, LLMs and optimization) that work well with CVS diverse product portfolio, develop robust methodologies to assess model performance
- Work cross functionally with a range of technical and non-technical stakeholders including business partners, engineers, and other data and analytics teams. Share progress, findings, recommendations, and their business implications. Present meaningful and insights-driven materials on analytical results with recommendations and go forward planning to guide a variety of audiences including internal stakeholders and senior leadership
Preferred Qualifications
- Work experience in consulting industry
- Demonstrated experience applying operations research, reinforcement learning, simulation, and/or dynamic programming techniques
- Hands on experience solving prioritization, scheduling or supply chain problems by building mathematical optimization models using open-source or commercial optimization solvers (such as Gurobi, Pulp, CPLEX)
- Experience with cloud computing platforms (e.g., GCP.), including querying/mining large datasets and deploying projects on cloud systems
- Familiarity with working in an Agile framework
