Manager, Data Science; Non-Financial Risk

Manager, Data Science (Non-Financial Risk)

Join to apply for the Manager, Data Science (Non-Financial Risk) role at KPMG US
. KPMG Advisory practice is currently our fastest growing practice, and we are looking for talented professionals who thrive in a collaborative, team‑driven culture.

• Serve as the technical lead on projects to design and develop advanced AI/ML solutions to meet clients’ unique requirements, including participation in internal and external discussions to gather business use case requirements, provide advanced analytics and data science expertise and solution options for business problems.
• Engineer solutions using natural language processing and machine learning techniques to solve critical problems and improve processes for clients across capital markets and financial services businesses, including trade surveillance, electronic communications surveillance, payments fraud detection, third‑party risk management and other operational risk categories.
• Utilize machine learning, natural language, and statistical analysis methods, such as sentiment analysis, topic modeling, time‑series analysis, regression, classification, statistical inference, and validation methods to review financial services client risks.
• Perform explanatory data analyses, generate and test working hypotheses; prepare and analyze historical data and identify patterns to develop innovative solutions to financial services operational risk and regulatory compliance programs.
• Lead technical teams, mentor junior data scientists, and grow data science expertise within the broader team, including offshore; collaborate with diverse, cross‑functional teams to accurately identify and prioritize requirements, ensuring that AI/ML solutions meet the needs and expectations of various stakeholders.
• Present to key stakeholders, such as approach, data requirements, interim findings, and final solution architecture and infrastructure.
• Act with integrity, professionalism, and personal responsibility to uphold KPMG’s respectful and courteous work environment.

• Minimum six years of recent professional experience working in advanced analytics and data science; minimum two years of recent experience managing teams and delivering complex and critical projects.
• Bachelor’s degree from an accredited college/university in a relevant STEM field (data science, computer science, engineering, mathematics, physics, or other related fields).
• Extensive experience in AI/ML algorithm development and data analysis including at least one of the following: NLP, time‑series analysis, predictive modeling; experience with scripting, data structures and algorithms and ability to work with large amounts of data.
• Experience in a statistical programming language (for example, R or Python) and related data science / machine learning packages (for example, Pandas, Scikit‑learn, PyTorch, Transformers).
• Excellent communication, written, presentation, and problem‑solving skills.
• Previous technical client service experience preferred.
• Ability to travel as required (based on location and clients served).
• Applicants must be authorized to work in the U.S. without the need for employment‑based visa sponsorship now or in the future; KPMG will not sponsor applicants for U.S. work visa status for this opportunity.

KPMG is an equal‑opportunity employer. KPMG complies with all applicable federal, state and local laws regarding recruitment and hiring. All qualified applicants are considered for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, citizenship status, disability, protected veteran status, or any other category protected by applicable federal, state and local laws.