Senior Data Scientist, Applied AI and Agentic Solutions Engineer

VSP Vision Care•Cynthian, OH

1d•$84,000 - $141,750

About The Position

Model complex business problems and discovering business insights using statistical, algorithmic, mining, and visualization techniques. The data scientist conducts experiments and methodologies to generate and collect data for business use. Mines available data to identify trends and patterns and generates insights for LOBs and senior leadership.

Requirements

Bachelor’s degree in computer science, data science, statistics, economics, or related functional area; or equivalent experience
6 years of demonstrated experience in any of the following areas: Analytics, Data Science, Machine Learning, AI Platform/Solution Development, Data & AI Engineering, Cloud Platform Engineering or related discipline
Flexible and able to change priorities and direction quickly and effectively
Excellent written and verbal communication, presentation and analytical skills
Strategic skills, business acumen and curiosity to support envisioning work, program planning and strategic partnerships
Ability to regularly exercise discretion and independent judgment in the performance of his/her job duties
Remain current in the field, including new techniques, approaches, and software available

Nice To Haves

Experience developing and deploying AI, generative AI, and analytics solutions that enable enterprise knowledge discovery, automation, and decision support.
Experience partnering across the full solution lifecycle, including requirements gathering, design, development, testing, implementation, and end-user adoption.
Demonstrated ability to deliver scalable, secure, and maintainable solutions leveraging generative AI, intelligent agents, and advanced analytics technologies.
Proficiency with modern application development technologies such as Python, React, TypeScript, Node.js, APIs, and data visualization frameworks.
Experience designing and implementing AI-enabled solutions using large language models (LLMs), machine learning capabilities, vector embeddings, semantic search, Snowflake Cortex, and other emerging AI technologies.
Experience building and deploying Retrieval-Augmented Generation (RAG) solutions, including document ingestion, data chunking, embeddings, vector databases, retrieval strategies, prompt engineering, and response generation.
Ability to evaluate and optimize AI-generated outputs for accuracy, reliability, performance, security, and overall business value.
Experience utilizing AI-assisted development tools and modern engineering practices to improve productivity while maintaining high standards for code quality, testing, security, and maintainability.
Knowledge of performance monitoring, observability, reliability, scalability, and operational support for AI and analytics solutions in production environments.
Understanding of security, privacy, governance, responsible AI principles, and compliance considerations related to AI and analytics development.
Experience working with cloud-based AI, analytics, and data platforms in enterprise environments.
Strong collaboration and communication skills with the ability to translate business needs into technology solutions.

Responsibilities

Partners with LOBs to identify questions and issues for data analysis and experiments
Performs complex statistical analysis on experimental or business data to validate and quantify trends or patterns
Constructs predictive models, algorithms, and probability engines to support data analysis or product functions; verifies model and algorithm effectiveness based on real-world results
Identifies meaningful insights from large data and metadata sources; interprets and communicates insights and findings from analysis and experiments to product, service, and business managers
Develops and codes software programs, algorithms, and automated processes to cleanse, integrate, and evaluate large datasets from multiple disparate sources
Researches and applies knowledge of existing and emerging data science principles, theories, and techniques to inform business decisions
Uses advanced mathematical and statistical concepts and theories to analyze and collect data and construct solutions to business problems
Participates in research and implements cutting-edge techniques and tools in machine learning/deep learning/artificial intelligence to make data analysis more efficient and to create new data-driven capabilities and insights
Supports user experience specialists and information architects to enhance information visualization through development of dashboards and user interface best practices to analytics and product teams and provides consultations for their data-based experimentations
Assists in communicating Enterprise data governance principles throughout the company