Sr. Data Scientist - Credit Risk (IITs/NITs/BITs)

Time Hack Consulting; Maharashtra; Vor Ort; INR 1.200.000 - 1.800.000; Vollzeit

Benefits dieser Stelle

Hands-on ownership of high-impact projects

Mentorship-driven environment

Opportunities to work on regulatory-compliant implementations

Zusammenfassung

A leading consulting firm in India seeks an experienced professional for a senior role focused on building production-ready credit-risk models. You will lead model development, implement validation frameworks, and collaborate with engineering to deploy machine learning solutions. Ideal candidates have a strong background in Python, SQL, and advanced statistical modeling. The position offers a mentorship-driven culture with exposure to high-impact projects and client interactions.

Qualifikationen

• Experience with model monitoring and MLOps tooling (CI/CD for models, Airflow).
• Knowledge of regulatory frameworks (Basel II/III, IRB) and model governance.
• Familiarity with cloud platforms (AWS/GCP/Azure) for data and model deployment.

Aufgaben

• Lead end‑to‑end development of credit‑risk models including data sourcing, feature engineering, and model documentation.
• Design and implement model validation, back-testing, and performance monitoring frameworks.
• Productionize ML models and build scalable pipelines in collaboration with engineering.

Kenntnisse

Python

SQL

PySpark

scikit-learn

XGBoost

PD/LGD/EAD modelling

Ausbildung

Educational background from IITs/NITs/BITs or equivalent technical institutions

Jobbeschreibung

About The Opportunity

A consulting firm operating at the intersection of financial services and credit risk analytics. We deliver end‑to‑end credit decisioning, risk‑model development, and regulatory‑compliant analytics for banks, NBFCs and fintech lenders. This is an on‑site senior role in India focused on building production‑ready credit‑risk models and scalable ML pipelines.

Role & Responsibilities

• Lead end‑to‑end development of credit‑risk models (PD/LGD/EAD): data sourcing, feature engineering, model building, benchmarking and documentation.
• Design and implement robust model validation, back‑testing and performance monitoring frameworks aligned to model‑risk governance and regulatory expectations.
• Productionize ML models: build scalable pipelines (PySpark/Python), collaborate with engineering to deploy models and automate scoring in lending platforms.
• Apply advanced machine learning (tree‑based ensembles, stacking, calibrated probabilities) to improve discrimination and calibration for scorecards and risk ranking.
• Partner with stakeholders (product, analytics, compliance) to translate business requirements into model objectives and measurable KPIs.
• Mentor junior analysts, define modelling best‑practices and contribute to model risk documentation and audit‑ready deliverables.

Skills & Qualifications

Must‑Have

• Python
• SQL
• PySpark
• scikit‑learn
• XGBoost
• PD/LGD/EAD modelling

Preferred

• Experience with model monitoring and MLOps tooling (CI/CD for models, Airflow)
• Knowledge of regulatory frameworks (Basel II/III, IRB) and model governance
• Familiarity with cloud platforms (AWS/GCP/Azure) for data and model deployment

Additional Qualifications

• Proven track record in building credit‑risk models for retail, SME or corporate lending portfolios.
• Strong analytical rigor with experience in statistical validation, uplift testing and calibration techniques.
• Preferred: educational background from IITs/NITs/BITs or equivalent technical institutions.
• This is an on‑site position based in India; ability to work closely with cross‑functional teams and attend client meetings is required.

Benefits & Culture Highlights

• Hands‑on ownership of high‑impact credit‑risk projects and visible client exposure.
• Mentorship‑driven environment with focus on technical excellence and model governance maturity.
• Opportunities to work on regulatory‑compliant implementations and scale models into production.

Skills: python, modelling, scorecards, credit risk, sql

Seniority level

• Mid‑Senior level

Employment type

• Full‑time

Job function

• Engineering and Information Technology

Industries

• Business Consulting and Services