Data Scientist II
About The Position
Under general supervision, advances’ broad capabilities to use and deploy cutting edge data science and machine learning tools and methods in projects, platforms and products. Anchors current best practices by supporting the design and build of reusable data science assets. Simultaneously works to keep on the bleeding edge by understanding the very latest and most sophisticated methods and tools for grappling with extremely large scale and complex problems. Applies descriptive, diagnostic, predictive, prescriptive, and ensemble modeling, statistical techniques, machine learning methods, and AI-driven approaches to analyze complex business situations and support decision making. Provides recommendations to moderately complex issues through the application of data science, machine learning, Generative AI, and data engineering practices, leveraging data-driven insights to support business objectives. Works in tandem with peer data scientists, engineers, and business stakeholders to develop, test, and deploy end-to-end analytical, machine learning, and AI solutions. Assists in the development, evaluation, and deployment of machine learning, Generative AI, and LLM-based solutions, including experimentation, model validation, and performance monitoring.
Requirements
- Master’s degree (or equivalent) in Computer Science, Operations Research, Statistics, Applied Mathematics, or a related quantitative field.
- At least two (2) years of professional experience applying data science (e.g., machine learning, artificial intelligence, statistical analysis), operations research (e.g., optimization, algorithms, mathematical modeling), and data analytics to reduce costs, enhance profitability, and improve customer experience.
- An advanced degree in a related field may be considered in lieu of some experience.
Nice To Haves
- At least two (2) years of professional experience applying data science (e.g., machine learning, artificial intelligence, statistical analysis, Generative AI), operations research (e.g., optimization, algorithms, mathematical modeling), and data analytics to improve customer experience, reduce costs, enhance profitability, and solve business problems.
- Experience developing or supporting end-to-end analytics and machine learning solutions is preferred.
Responsibilities
- Advances broad capabilities to use and deploy cutting edge data science and machine learning tools and methods in projects, platforms and products.
- Supports the design and build of reusable data science assets.
- Understands the very latest and most sophisticated methods and tools for grappling with extremely large scale and complex problems.
- Applies descriptive, diagnostic, predictive, prescriptive, and ensemble modeling, statistical techniques, machine learning methods, and AI-driven approaches to analyze complex business situations and support decision making.
- Provides recommendations to moderately complex issues through the application of data science, machine learning, Generative AI, and data engineering practices, leveraging data-driven insights to support business objectives.
- Works in tandem with peer data scientists, engineers, and business stakeholders to develop, test, and deploy end-to-end analytical, machine learning, and AI solutions.
- Assists in the development, evaluation, and deployment of machine learning, Generative AI, and LLM-based solutions, including experimentation, model validation, and performance monitoring.
Benefits
- Pay Transparency
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
