Job description

KPMG is currently seeking a Data Scientist to join our Audit Technology Alliance organization. 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(200TEC)

Requirements

Must-haves

KPMG is currently seeking a Data Scientist to join our Audit Technology Alliance organization.
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
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(200TEC)

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimachine learningazurepythonagileci/cd

Platform: avature
Effort: medium