This position will serve as the analytics lead on data science projects with a focus on developing models and programs to manage Specialty Drug Costs. This incumbent will identify opportunities and use cases for integrating the newest data science algorithms and techniques to produce solutions. They will collaborate with other analytic and business areas including, but not limited to, Medical Economics, Actuary, Clinical Services, and Value Reimbursement Strategy and Innovation. They will serve as a Pharmacy data subject matter expert for enterprise analytic infrastructure changes
Essential Job Functions:
- Work directly with the business to understand their questions, business processes, programs and/ or initiatives, then identifying how analytical solutions could help deliver value for them (e.g., more effective and/ or efficient processes). This would include leading on and being accountable for, outlining new use cases, creating high level impact estimates, and identifying the necessary data elements (including proxies) to deliver the analytical solution. Assemble data sets using knowledge of where the required data exists within the Organization's source data system, derived production sets or publicly available sources. Includes securing appropriate access and documenting objectives, assumptions and processes.
- Select and apply the appropriate advanced modeling/machine learning techniques to these data sets to deliver business insight, ensuring that the final analysis is well researched, accurate, and documented. This requires technical flexibility, in-depth knowledge and delivery of advanced analytical approaches, for example regression models, tree-based learning, neural networks, clustering techniques, natural language processing.
- Consult with the business to contextualize and translate the results of our analysis in a form which the business can understand and take action on. This will be include written reports, presentation and data visualizations, and draws clear lines between the high-level problem specifications, the analyses performed, and how the results link directly back to business objectives. It requires data scientists to demonstrate their depth of understanding of many areas of the business, the data and the analytical methods through ongoing engagement with a range of audiences.
- Plan, prepare and deliver/coordinate all elements of the analysis in such a way that it is delivered on time, to a high standard and ready to implemented on a production basis (including dissemination through the Organization's user systems). This includes identifying the best route to implementation (developing the analytical solution accordingly).
- Research self- directed new analytical skills and approaches, building relationships internally and externally to transfer knowledge and maintain their position as subject matter experts, consult with follow data scientists and analysts to guide analysis and deliver larger projects.
- Other duties as assigned.
- Master's Degree in Analytics, Mathematics, Physics, Computer and Information Science or Engineering
- 3 - 5 years in Data Analytics
- 3 - 5 years using Large Datasets
- 3 - 5 years utilizing Statistical Software
- 3 - 5 years in Data Visualization
- 3 - 5 years in Predictive Modeling
- 1 - 3 years in the Healthcare Industry
- 1 - 3 years in Research and Development
- 1 - 3 years in a Business Analyst role
- 1 - 3 years in Consulting
- Doctorate degree in Analytics, Mathematics, Physics, Computer and Information Science, or Engineering
- Python and/or R
- Experience with version control systems, such as Gitlab/Github
- Comfortable with using unix/linux servers and basic terminal experience
- Experience with Spark and big data querying tools, such as Hive
- Proficiency with Hadoop, HDFS
Knowledge, Skills & Abilities:
- Collaborative Problem Solving
- Analytical and Logical Reasoning/Thinking
- Analysis of business problems/needs
- Written & Oral Presentation Skills
Referral Award Payout Level: 2
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