This role sits at the intersection of credit risk analytics, consulting, and client engagement, working closely with financial institutions to improve credit decisioning across the lending lifecycle.
You will partner with banks and financial services clients to translate business challenges into practical, datadriven credit risk solutions, while collaborating with internal sales and technical teams on solution design and delivery. The role offers strong exposure to client consulting, advanced analytics, and regional financial institutions.
What We're Looking For:
- Bachelor's degree in Statistics, Mathematics, Data Science, Economics, Finance, or related fields (Master's degree or MBA is a plus)
- 48 years of experience in credit risk analytics, modeling, or consulting within banks, financial institutions, fintechs, or consulting firms
- Strong understanding of lending products and the credit lifecycle (origination, customer management, collections)
- Experience with credit risk scorecards or predictive models is highly valued
- Strong analytical thinking with the ability to explain insights to nontechnical stakeholders
- Excellent communication and presentation skills
- Proficiency in Excel and PowerPoint
Nice to Have:
- Clientfacing consulting or solutioning experience
- Exposure to IFRS9 / ECL modeling
- Working knowledge of Python, R, or similar analytics tools
- Experience working with credit bureau or alternative data
Key Responsibilities
- Engage with clients to understand business objectives, lending strategies, and credit risk challenges
- Analyze client requirements through discussions, workshops, and RFPs
- Design and present credit risk analytics or advisory solutions across origination, customer management, and collections
- Provide recommendations to enhance existing credit risk practices, scorecards, or decisioning frameworks
- Support proposal development, including solution scope, delivery approach, and timelines
- Participate in presales discussions as a subject matter expert (not a sales quota role)
- Develop project plans and coordinate with internal analytics and delivery teams
- Define data requirements and assess data quality, structure, and usability
- Ensure project delivery meets agreed quality standards, timelines, and budgets
- Build trusted client relationships and identify opportunities for additional analytics or advisory support
