Data Scientist- Associate

Summary

KPMG US is a leading provider of audit, tax, and advisory services known for fostering a great work culture. They are seeking an Associate Data Scientist to develop and implement generative AI solutions, collaborate with engineers, and contribute to continuous improvement in their Audit Technology Alliance organization.

Responsibilities

• Develop and implement core components of generative AI solutions, including RAG pipelines and context engineering features, within our established architecture; driving quality into prompt engineering and optimization for business use cases
• Support senior team members in the implementation of RAG pipelines and context engineering systems by building and testing specific modules
• Collaborate with AI engineers and other data scientists to integrate model outputs into the broader microservice architecture
• Focus on learning and applying our technology stack, including LangChain/LangGraph, Azure AI Search, and our AKS-based infrastructure
• Drive product advancement by diligently executing experiments, documenting results, and contributing to our culture of continuous improvement
• Participate actively in agile ceremonies and contribute to the team's collective knowledge of generative AI, audit methodologies, and best practices
• Act with integrity, professionalism, and personal responsibility to uphold KPMG's respectful and courteous work environment

Skills

• Minimum one year of experience or strong internship/academic projects in data science, machine learning, or software engineering
• Minimum of a Bachelor's degree is required
• Foundational knowledge of machine learning concepts and Python for data analysis; familiarity with LLMs and frameworks like LangChain is preferred
• Exposure to cloud platforms (preferably Azure) and data platforms like Databricks or Microsoft Fabric
• Familiarity with the principles of the software development lifecycle (SDLC) and version control tools like ADO and Github
• Strong analytical and problem-solving skills, with an eagerness to learn and a collaborative, team-oriented mindset (200TEC)
• Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)
• Master's degree from an accredited college or university in Computer Science, Data Science, Statistics, or a related quantitative discipline is preferred
• Familiarity with LLMs and frameworks like LangChain is preferred

Qualifications

Must Haves

• Minimum one year of experience or strong internship/academic projects in data science, machine learning, or software engineering
• Minimum of a Bachelor's degree is required
• Foundational knowledge of machine learning concepts and Python for data analysis; familiarity with LLMs and frameworks like LangChain is preferred
• Exposure to cloud platforms (preferably Azure) and data platforms like Databricks or Microsoft Fabric
• Familiarity with the principles of the software development lifecycle (SDLC) and version control tools like ADO and Github
• Strong analytical and problem-solving skills, with an eagerness to learn and a collaborative, team-oriented mindset (200TEC)
• Must be authorized to work in the U.S. without the need for employment-based visa sponsorship now or in the future. KPMG LLP will not sponsor applicants for U.S. work visa status for this opportunity (no sponsorship is available for H-1B, L-1, TN, O-1, E-3, H-1B1, F-1, J-1, OPT, CPT or any other employment-based visa)

Nice to Haves

• Master's degree from an accredited college or university in Computer Science, Data Science, Statistics, or a related quantitative discipline is preferred
• Familiarity with LLMs and frameworks like LangChain is preferred

Benefits

• Medical and dental plans
• Vision coverage
• Disability and life insurance
• 401(k) plans
• A robust suite of personal well-being benefits to support your mental health
• Personal Time Off per fiscal year
• Calendar of holidays to be observed during the year
• Two breaks each year where employees will not be required to use Personal Time Off