Data Scientist- Manager

Responsibilities

• Develop sophisticated generative AI solutions; provide technical guidance to a team of data scientists
• Guide the end-to-end data science lifecycle for key product features; oversee experimentation, rigorous model evaluation, and prompt engineering and optimization
• Collaborate closely with product managers, audit subject matter experts, and engineering teams to translate complex business requirements into scalable and reliable technical solutions
• Champion a culture of quality and innovation within engineering teams; identify opportunities to continually improve solutions
• Drive quality SDLC processes with AI engineering teams; deliver solutions on time to meet business cycle timelines
• Champion and enhance AI and RAG evaluation frameworks using tools like LangSmith; ensure solutions meet KPMG's standards for quality
• Provide technical leadership and mentorship to junior data scientists; guide hands-on work in context engineering, model tuning, and advanced data analysis
• Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment

Qualifications

• Minimum five years of recent experience in data science or a related machine learning field with a proven track record of delivering AI solutions into production environments
• PhD or Master's degree from an accredited college or university in computer science, statistics, mathematics, or a related quantitative discipline is required
• Hands-on expertise with generative AI including extensive experience with LLMs (for example, Azure OpenAI, Google Cloud), RAG pipelines, and AI frameworks such as LangChain/LangGraph or Semantic Kernel
• Proficient in Python and its data science ecosystem; experienced in building solutions on data platforms like Databricks or Microsoft Fabric and search technologies like Azure AI Search
• Solid understanding of the software development lifecycle (SDLC) in an agile environment; experienced with version control tools like Git and CI/CD tools within Azure DevOps
• Exceptional analytical skills; able to communicate complex technical concepts clearly and effectively to both technical and non-technical stakeholders