Consultant, Data Science -Credit Risk

TransUnion; Pune District; On-site; INR 1,800,000 - 2,600,000; Full time

Job summary

TransUnion is seeking a seasoned Credit Risk Analytics professional to partner with banks and financial institutions, designing and deploying predictive scorecards and risk models. You will analyze large datasets using Python and SQL, translate findings into actionable recommendations for senior stakeholders, and monitor model performance across lifecycle stages.

The role involves collaborating with global teams to deliver high-impact engagements and contribute to risk strategy development for

Qualifications

• 4+ years of experience in Credit Risk Analytics, Risk Consulting, Banking Analytics, or Financial Services Analytics.

Responsibilities

• Identify and solve credit risk problems for banks and financial institutions.
• Develop and enhance scorecards for lending and portfolio decisions.
• Design and deploy predictive risk models using statistical techniques and ML.
• Analyze large datasets with Python/SQL and communicate actionable insights to stakeholders.
• Monitor model performance, back-testing, and validation to ensure effectiveness.
• Collaborate with global teams to deliver high-impact client engagements.

Skills

Python

SQL

Logistic Regression

ML techniques

Model validation

Education

Statistics/Mathematics/Economics/Engineering/CS/Data Science (Bachelor's/Master's)

Job description

The Credit Risk Consulting team partners with leading financial institutions across the US and Africa to solve complex lending, portfolio management, and risk strategy challenges through advanced analytics and data-driven decisioning. Working at the intersection of consulting, credit risk, and machine learning, the team helps clients improve profitability, manage risk exposure, optimize customer acquisition, and drive sustainable business growth.

Role Overview and Core Responsibilities

• Partner with banks, lenders, and financial institutions to identify, structure, and solve complex credit risk business problems.
• Develop and enhance application, behavioral, acquisition, collections, and account management scorecards that drive lending and portfolio decisions.
• Design and deploy predictive risk models using statistical techniques and Machine Learning (ML) methodologies.
• Utilize Python, SQL, and advanced analytics techniques to analyze large customer and portfolio datasets and generate actionable insights.
• Translate business requirements into analytical solutions and communicate recommendations to senior client stakeholders.
• Conduct model performance monitoring, validation, back-testing, and champion-challenger analysis to ensure model effectiveness.
• Collaborate with global consulting, analytics, and product teams to deliver high-impact client engagements across US and Africa regions.
• Support risk strategy development across customer lifecycle stages, including acquisition, portfolio management, collections, and fraud mitigation.
• Present findings, recommendations, and strategic insights to business leaders and client executives.
• Contribute to thought leadership, innovation initiatives, and development of next-generation risk analytics capabilities.

Required Knowledge and Experiences

• 4+ years of experience in Credit Risk Analytics, Risk Consulting, Banking Analytics, or Financial Services Analytics, with demonstrated experience applying analytical solutions to business problems.
• Strong understanding of retail lending portfolios, credit risk frameworks, scorecard development, and customer lifecycle risk management.
• Experience developing and implementing statistical or predictive models to support credit decisioning and portfolio performance.
• Proven ability to work directly with business stakeholders and translate analytical findings into actionable business recommendations.
• Bachelor's or Master's degree in Statistics, Mathematics, Economics, Engineering, Computer Science, Data Science, or a related quantitative discipline, or equivalent professional experience.

Required Technical Skills

• Strong Python programming skills for data analysis, model development, feature engineering, and automation.
• Advanced SQL expertise for data extraction, transformation, validation, and analysis of large datasets.
• Hands-on experience developing scorecards using Logistic Regression and other predictive modeling techniques.
• Experience applying Machine Learning (ML) techniques such as Gradient Boosting, Random Forest, XGBoost, or related methodologies within risk analytics environments.
• Proficiency with statistical analysis, model validation, model monitoring, and performance measurement techniques.

We're also looking for the preferred skills below. Whether you are proficient or could use some brushing up, we're happy to support your career development and growth in:

• Experience supporting consulting engagements for global banking and financial services clients.
• Exposure to Basel frameworks, model governance, model risk management, and regulatory requirements.
• Experience working with African, North American, or other international lending markets.
• Knowledge of cloud-based analytics environments and modern data ecosystems.
• Experience mentoring junior analysts and contributing to capability-building initiatives.

Why Join This Team

• Solve strategic business challenges for leading global financial institutions.
• Work on high-impact consulting engagements across diverse lending markets.
• Blend consulting, advanced analytics, machine learning, and credit risk expertise in a single role.
• Influence risk strategy, customer growth, and portfolio performance for clients worldwide.
• Collaborate with a highly skilled global team of consultants, data scientists, and credit risk experts.