Credit Risk Modeling Lead

EXL; San Francisco (CA); On-site; USD 180,000 - 240,000; Full time

Job summary

EXL is seeking a seasoned Machine Learning Modeling Lead - Credit Modeling to spearhead the ML Model Innovation team in the banking/fintech domain (digital lending). The role drives end-to-end ML solution development from data exploration and feature engineering through model deployment and monitoring in production environments.

The candidate will lead junior scientists and engineers, collaborate with cross-functional teams, and ensure robust, compliant models for credit scoring, collections,

Qualifications

• Master’s or similar in Computer Science, Data Science, Statistics, Applied Mathematics or related field.
• 10+ years of experience in applied ML model development in banking/fintech or financial services.
• Proven leadership of ML projects and teams.
• Experience with model development, deployment and monitoring in production.
• Familiarity with collections, underwriting, fraud and ethical considerations in banking ML models.

Responsibilities

• Lead end-to-end ML solution development and innovation from data exploration to deployment and monitoring.
• Develop robust models to drive business benefits and review junior submissions.
• Oversee documentation, model reviews and validation responses.
• Collaborate with validation teams to address model queries.
• Work with implementation teams to deploy models in cloud or on-premises.
• Translate banking domain challenges into data-driven solutions with stakeholders.
• Mentor junior data scientists and engineers on best practices.
• Continuously evaluate new tools and frameworks in finance ML.
• Publish internal research and promote a culture of experimentation.

Skills

Python

SQL

ML libraries

MLOps

Leadership

Communication

Education

Master's in Computer Science / Data Science / Statistics / Applied Mathematics

Tools

MLflow

Kubeflow

Airflow

Docker

Kubernetes

Job description

We are seeking a highly skilled and experienced Machine Learning Modeling Lead - Credit Modeling to join our ML Model Innovation team within the banking/fintech domain (digital lending). The ideal candidate will be responsible for leading the development and deployment of machine learning models that power key business decisions such as collections models, credit risk scoring, fraud detection, customer segmentation, and personalized financial services.

The Individual needs to have strong knowledge of banking business, data and domain across the customer lifecycle as well as bureau data. They will collaborate with cross-functional teams and provide technical leadership to junior ML modelers and data scientists.

Key Roles and Responsibilities -

• Lead end-to-end ML solution development & innovation from data exploration, feature engineering, model development, validation, deployment, and monitoring.
• Develop robust models which can drive business benefits. Support and review junior scientist submissions and share enhancement suggestions
• Responsible for documentation/documentation reviews, model reviews and submission
• Responsible for managing queries raised by Validation teams for the model
• Collaborate with implementation teams to deploy models into production environments (cloud or on premises).
• Work closely with business stakeholders to translate banking domain challenges into data-driven solutions.
• Guide junior data scientists and engineers on best practices in model development
• Continuously evaluate new tools, technologies, and frameworks relevant to ML in finance.
• Publish internal research and promote a culture of innovation and experimentation.

Candidate Profile:

• Strong business knowledge of banking analytics across the retail banking customer lifecycle.
• 9+ years of experience in applied machine learning model development in the banking or financial services domain.
• Hands-on experience leading ML projects and teams.
• Strong experience with model development, deployment and monitoring in production environments.
• Familiarity with collections, underwriting, fraud and ethical considerations in banking ML models.
• Demonstrable leadership ability, superior problem solving and people management skills
• Master’s or Similar in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative field

Skills:

• Expert in Python, SQL, ML libraries (Numpy, Pandas, Scikit-learn, TensorFlow, PyTorch) and techniques (Regression, Decision Trees, Ensembles: XGBoost, GBM, Random Forest, Unsupervised Learning, etc.).
• Knowledge of MLOps frameworks (MLflow, Kubeflow, Airflow, Docker, Kubernetes) is added benefit.
• Strong grasp of statistical modeling, optimization, and deep learning techniques.
• Excellent communication skills and ability to explain complex concepts to non-technical stakeholders.

What we offer:

• EXL Analytics offers an exciting, fast paced and innovative environment, which brings together a group of sharp and entrepreneurial professionals who are eager to influence business decisions. From your very first day, you get an opportunity to work closely with highly experienced, world class analytics consultants.
• You will learn effective teamwork and time-management skills - key aspects for personal and professional growth
• Analytics requires different skill sets at different levels within the organization. At EXL Analytics, we invest heavily in training you in all aspects of analytics as well as in leading analytical tools and techniques.
• We provide guidance/ coaching to every employee through our mentoring program wherein every junior level employee is assigned a senior level professional as advisors.
• Sky is the limit for our team members. The unique experiences gathered at EXL Analytics sets the stage for further growth and development in our company and beyond.