Job Description

Role Overview

We are seeking a

Vice President of Data Science

with deep, hands-on expertise in

AI/ML modeling for U.S. consumer credit-card and subprime lending portfolios

.
The ideal candidate combines

technical mastery

,

business intuition

, and

execution capability

, with the ability to both

build models personally

and

lead a small, high-performing data science team

(3-5 members).This leader will design, develop, and deploy advanced ML solutions that power

credit underwriting, collections optimization, and marketing targeting

, leveraging both

internal portfolio data

and

third-party data sources

(paid and free).
The focus is on delivering measurable business impact--better credit decisions, higher recovery rates, and improved customer lifetime value.

Key ResponsibilitiesAI/ML Model Development & Delivery

Lead the end-to-end development of

predictive and prescriptive ML models

for credit underwriting, collections, and marketing. Build

forecast-based and behavioral scoring models

to predict payment capacity, delinquency likelihood, and offer responsiveness. Utilize supervised and unsupervised ML techniques (regression, ensemble methods, clustering, survival analysis, NLP, etc.) to enhance decision quality. Prototype, test, and productionize models using Python, SQL, and cloud ML frameworks (AWS SageMaker, Azure ML, or GCP Vertex).

Data Management & Feature Engineering

Design robust

feature stores

integrating internal portfolio data (applications, payments, transactions) with external third-party data. Evaluate, source, and integrate

third-party and alternative datasets

--credit bureau, bank transaction, device, telecom, social, and open data sources. Maintain awareness of

free and paid data providers

, assessing their predictive lift and ROI for subprime segments.

Cross-Functional Collaboration

Partner with Credit, Collections, and Marketing teams to

translate model outcomes into decision rules

that can be operationalized. Work with Engineering and Product teams to

deploy models into production

, monitor performance, and retrain as needed. Support CFO, CRO, and business heads with

portfolio risk forecasting, stress testing, and loss analytics.

Governance & Compliance

Ensure compliance with

U.S. consumer-lending regulations

(FCRA, ECOA, FDCPA, UDAAP) and

model governance frameworks (SR 11-7)

. Document methodologies, validation results, and model assumptions to support regulatory and investor transparency. Partner with internal model-validation and compliance teams for ongoing reviews.

Leadership & Mentorship

Lead, mentor, and grow a

3-5 member data science team

, setting clear technical and business objectives. Create a culture of analytical rigor, experimentation, and continuous learning. Provide thought leadership in ML methodology, data-driven decisioning, and cross-functional impact measurement.

Qualifications

12-18 years

of experience in applied data science or machine learning, with

significant exposure to U.S. consumer credit-card or subprime lending portfolios

. Proven expertise building

credit-risk, collections, or marketing response models

in production environments. Strong understanding of

consumer credit data

, loss forecasting, and collection-behavior dynamics. Proficiency in

Python, SQL, and ML libraries

(scikit-learn, XGBoost, LightGBM, PyTorch/TensorFlow optional). Deep knowledge of

third-party data ecosystems

(Experian, Equifax, TransUnion, LexisNexis, Neustar, Plaid, Socure, etc.) and alternative data APIs. Experience deploying models through

cloud-based MLOps pipelines

and working in agile delivery setups. Master's or Ph.D. in

Statistics, Computer Science, Machine Learning, Economics, or related quantitative discipline

.

Preferred Attributes

Strong understanding of

subprime customer behavior

and

credit-cycle dynamics

. Track record of delivering

quantifiable financial impact

(e.g., 20% improvement in collections yield, 15% charge-off reduction, 2-3x lift in marketing ROI). Excellent communication and presentation skills; able to explain model logic to executives and non-technical stakeholders. Ability to thrive in a fast-paced environment with a small, expert team and high ownership.
Job Type: Contractual / Temporary
Contract length: 6 months

Pay: ₹400.00 - ?600.00 per hour

Expected hours: 28 per week

Experience:

Data Science (AI/ML, Credit, Collections & Marketing): 10 years (Required)
Work Location: Remote