About this role
Job Summary:
Solves complex analytical problems using quantitative approaches through a combination of analytical, mathematical and technical skills. Researches, designs, implements and validates complex algorithms to analyze diverse sources of data to achieve targeted outcomes by leveraging complex statistical and predictive modeling concepts.
Key Responsibilities:
Participates in projects to support key objectives and business goals through the use of data science methodology. Leverages data science methodology to solve complex business problems. Creates multiple algorithms using complex statistical methodologies through the use of statistical programming languages and tools. Partners with domain experts to verify model capabilities. Partners with Solution Architect to enable appropriate data flow/data model, development using appropriate tools/technology, rapid prototyping and informs the design of analytical products. Partners with less experienced employees on data science tools and methodologies. Clearly articulates results, methodologies and learnings to stakeholder and peer group. Continuous development and advancement of the team through knowledge sharing and collaboration.
Core Responsibilities Unique to the Role
*** Lead AI, Generative AI, and advanced analytics innovation initiatives by researching, evaluating, prototyping, and industrializing emerging AI capabilities that improve business outcomes, accelerate data product adoption, and create reusable enterprise assets across Supply Chain, Quality, Finance, and Engineering domains.
*** Drive AI-enabled productivity and development lifecycle acceleration by implementing intelligent automation, agentic AI, code generation, automated testing, knowledge retrieval, and AI-assisted decision support solutions that reduce software delivery effort, improve engineering productivity, and enhance operational effectiveness.
*** Develop scalable enterprise AI capabilities using Data Products as the foundation by partnering with Product Managers, Data Engineers, and Solution Engineers to leverage Snowflake, Databricks, enterprise data products, and cloud AI platforms to build production-ready AI solutions that can be reused across business functions.
Required Skills, Education, or Experience
*** Experience developing and deploying Machine Learning, Generative AI, Large Language Model (LLM), Natural Language Processing (NLP), and advanced analytics solutions in enterprise environments.
*** Hands-on experience with modern AI and data platforms including Databricks, Snowflake, MLFlow, Azure OpenAI, Azure AI Services, vector databases, and scalable model deployment frameworks.
*** Strong understanding of modern AI solution patterns including Retrieval-Augmented Generation (RAG), semantic search, vector search, agentic AI, prompt engineering, model evaluation, fine-tuning approaches, and responsible AI practices.
*** Ability to identify high-value business opportunities and translate them into measurable outcomes including productivity gains, automation benefits, cycle-time reduction, cost optimization, improved decision-making, and enhanced customer experiences.
*** Bachelor’s degree in Data Science, Computer Science, Artificial Intelligence, Engineering, Mathematics, Statistics, or equivalent practical experience.
Preferred (Nice to Have) Skills, Education, or Experience
*** Experience implementing AI solutions using Databricks Lakehouse, Mosaic AI, MLFlow, Delta Lake, Feature Store, Model Serving, Snowflake Cortex AI, Snowpark, and Vector Search capabilities.
*** Experience building AI-powered engineering productivity solutions including developer copilots, intelligent assistants, automated testing frameworks, documentation generation, enterprise knowledge management platforms, and agentic workflow automation.