Responsibilities:
- To convert business problems into an analytics solution using their consulting skills, business knowledge to analyze client business issues, formulate hypotheses and test conclusions to determine appropriate solutions methods. A solid foundation typically in statistics, modeling, operations research, computer science and applications, and math.
- Strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge. Will not just address business problems, but pick the right problems that have the most value to the organization.
- Effective at deploying an analytics solution, thereby realizing business value. To explore and examine data from multiple disparate sources and to extract, transform, and combine all incoming data with the goal of discovering a previously hidden insight, which in turn can provide a competitive advantage or address a pressing business problem.
- Builds statistical models, determines what it means, then recommends ways to apply the data. To be inquisitive: exploring, asking questions, doing "what if" analysis, questioning existing assumptions and processes.
- Armed with data, modeling expertise, and analytical results, communicate informed conclusions and recommendations across an organization's leadership structure. Focuses on Individual/Team Objectives and Developing Professional Effectiveness.
Requirements:
- Strong AI/Gen AI development experience required
- Knowledge and experience on LLM, Langchain/Langgraph/Langsmith, Agentic Workflow, RAG with Text embedding/vector db, and related Gen AI technologies preferred
- Python experience is a must
- Good English skill is a must
- K8S experience is a must
- Microservices engineering experience is a must
- Strong and creative problem solving skills required
- Java experience is a big plus
