Position Summary:
The Lead Analyst uses specialized depth and experience to develop and modify complex software application programs supporting Machine Learning and Artificial Intelligence initiatives. This position will be responsible for advocating, educating and ensuring that machine learning (ML) teams across the enterprise are following best practices around the preferred technology stacks, as well as implementing Machine Learning applications and proof of concepts (POC). As a member of the newly formed Machine Learning Center of Excellence, This position will also create detailed specifications, conduct quality assurance reviews of peer’s application programming, and act as a resource for team members with less experience.
Key Responsibilities:
- Consult to product development team’s best practices related to Machine Learning application development and Machine Learning/AI-specific infrastructure technology stacks (e.g. GPU-based systems, A.I. in public cloud, etc).
- Determine root cause of problems and drive resolution
- Create Machine Learning Solutions to achieve organizational objectives
- Apply best practice software engineering principles towards the development of applications, in order to productionalize Machine Learning models produced by Data Scientists and ML Engineers
- Implement actions to increase ESI and vendor partner knowledge on team
- Develop standard practices, components, guidelines for use of complex technology components
- Ensure quality of technology delivery of multiple vendors’ technology solutions for multiple concurrent projects or programs for an application family
- Resolve urgent and high production incidents
- Deliver solutions for multiple concurrent projects
- Identify and implement process enhancement opportunities associated with supporting the application area
- Provide technical guidance to projects/programs for complex components of a multiple technology suites
Required Education & Experience:
- Computer science fundamentals: data structures, algorithms, performance complexity, and implications of computer architecture on software performance (e.g., I/O and memory tuning)
- Adaptability and willingness to lean new tools and applications
- Proven ability to leverage Big Data and Data Science tools such as Python and SQL. Experience with related tools and languages (Hadoop, Spark, R, etc) highly desired
- Ability to work a flexible schedule to accommodate project deadlines
- Complete understanding and wide application of technical principles, theories and concepts in the field
- Strong customer service focus
- 2+ years experience and proven expertise in Machine Learning and Data Science areas
- Familiarity with health care or PBM industry highly desired