Machine Learning Modeler Lead – Banking

Job Title: Machine Learning Modeler Lead – Banking & Financial Services

Locatio
n: [Hybrid – GGN/BLR, WFH

]Departmen
t: Data Science / AI & Advanced Analytic

sEmploymen
t Type: Full-tim

**e

Job Summary**

-

We are seeking a highly skilled and experienced Machine Learning Modeling Lead to join our ML Model Innovation team within the banking domain (both retail transactional and 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/external data. He/she will collaborate with cross-functional teams and provide technical leadership to other ML modelers and data scientis

**ts.

Key Roles and Responsibilit**
i

• es -Minimum Years of Experience: 8+ years in Retail ban
• kingDeep business expertise of the different business lines in the Retail banking Credit risk space across the customer lifecycle. Good hands-on knowledge of Banking strategies around Underwriting, Collection & Recoveries, High-Risk Account Management (HRAM) and ECM Strateg
• ies.Knowledge of Fraud strategy and analytics in Retail banking domain an added advant
• age.Possesses end-to-end hands-on ML solution development experience, from data exploration, feature engineering, model development to validation, deployment and monitor
• ing.Develop robust models to solve across the spectrum business problems and drive business benefits. Support and review junior data scientists' submissions and share enhancement suggest
• ionsResponsible for documentation / reviews, model reviews and submis
• sionResponsible for managing queries raised by the model validation teams and defending the model/solution against internal MRM/audit te
• ams.Collaborate with implementation teams to deploy models into production environments (cloud or on-premis
• es).Work closely with business stakeholders to translate banking domain challenges into data-driven soluti
• ons.Guide junior data scientists and engineers on best practices in model development and M
• LOpsContinuously evaluate new tools, technologies, and frameworks relevant to ML in fina

• nce.Publish internal research and promote a culture of innovation and experimentat

• **ion.

Qualifications Educ**
a

• tion:

Master's or Similar in Computer Science, Data Science, Statistics, Applied Mathematics, or a related quantitative

• **field

Expe**
rience :Strong business knowledge of banking analytics across the retail banking customer lif
- ecycle.8+ 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 enviro
- nments.Familiarity with underwriting, collections, ECM, fraud and ethical considerations in banking ML

• models
  .

• Skills:

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

eholders.