Senior Data Scientist

Please find details for this position below: Client: Banking/Financial Industry Title: Senior Data Scientist - 4 Openings Location: Charlotte, NC / Irving, TX / Chandler, AZ, MN – Hybrid Roles Duration: 12+ Month (s) Extend or Convert based on performances Screening Questions: When the agent interprets user queries and writes its own SQL query to connect to salesforce database, how do you make sure the agent (LLM) can write the correct SQL, given so much details in the database table? When SQL data is returned, does LLM see them one more time and generalize the answer, or return the data directly to user? When design RAG, what are key considerations? Job Details: • Client is seeking a level 4 Data Scientist role to join Commercial Banking Model Development. • This role is pivotal in accelerating the design, development, and implementation of cutting-edge Generative AI (GenAI) and Agentic solutions within Commercial Banking. • The successful candidate will optimize model development and implementation for GenAI/Agentic use cases, work with a team of data scientists and collaborate with business and technology partners to drive end-to-end solution design and development for content extraction, summarization, generation, automation use cases using agentic frameworks, build and deploy LLM evaluation framework, build and reuse prompt libraries at scale to improve employee/customer experience, drive operational efficiencies, drive growth, and mitigate risks. • Working with data, platform, and technology partners, this role will accelerate and optimize design and delivery of GenAI and Agentic solutions by ensuring data, utilities, capabilities, and best practices are available on-prem and in the cloud. Required Qualifications: • Strong full stack data science skills, hands on experience with ADK, MCP, A2A, O2A. LLM evaluation framework, design and develop LLM guardrails, assertions, controls, and performance monitoring • Proficiency in Python, PySpark, TensorFlow, PyTorch, and cloud platforms such as Google Cloud Platform (GCP), Vertex AI, Google ADK, MCP. • Strong background in GenAI, Agentic workflow, machine learning, deep learning, and statistical analysis evidenced by successful deployment at scale • 7+ years of Quantitative Analytics experience • Master's degree or higher in a quantitative discipline such as mathematics, statistics, engineering, physics, economics, or computer science Desired Qualifications: • Experience in the financial services industry, Commercial Banking a plus • Familiarity with regulatory and compliance considerations in GenAI/AI model deployment • Strong communication and presentation skills with the ability to translate complex technical concepts to non-technical stakeholders EEO: Mindlance is an Equal Opportunity Employer and does not discriminate in employment on the basis of – Minority/Gender/Disability/Religion/LGBTQI/Age/Veterans.