Inviting applications for the role ofLead Data Scientist Collections Analytics

We are looking for an experienced Data Scientist/Data Analytics Expert to support the Project by developing, enhancing, and optimizing predictive analytics solutions for collections and customer engagement.

Key Responsibilities

- Design, develop, validate, and deploy machine learning models for collections analytics.
- Perform data exploration, feature engineering, model training, validation, and performance monitoring.
- Build scalable and production-ready machine learning pipelines.
- Collaborate with business stakeholders, data engineers, and analytics teams to translate business requirements into analytical and machine learning solutions.
- Evaluate and improve model performance using appropriate machine learning techniques and evaluation metrics.
- Document model development processes, assumptions, methodologies, and deployment artifacts.
- Support continuous model monitoring and enhancements based on business feedback and performance.

Required Skills

- Strong hands-on experience in Machine Learning, predictive analytics, and statistical modelling.
- Proficiency in Python and machine learning libraries/frameworks such as Scikit-learn, XGBoost, LightGBM, CatBoost, TensorFlow, or PyTorch.
- Experience in feature engineering, model evaluation, hyperparameter tuning, and model explainability.
- Strong understanding of supervised learning techniques, including classification, regression,



and ensemble methods.
- Hands-on experience with SQL and working with large, structured datasets.
- Good understanding of model deployment, monitoring, and ML Ops practices.

Preferred Skills

- Experience in the Banking, Financial Services (BFSI), or Collections domain.
- Hands-on experience developing machine learning or advanced analytics solutions for collections, customer engagement, or risk management.
- Experience working on one or more of the following use cases:
- Propensity to Pay
- Best Time to Call
- Right-Party Contact
- Contact Strategy Optimization
- Customer Segmentation or Behavioural Modelling
- Exposure to cloud platforms such as AWS, Azure, or GCP is an added advantage.
- Familiarity with GenAI/LLMs is a plus; however, the primary requirement is robust expertise in traditional Machine Learning and predictive analytics.

Qualifications we seekin you!

Domain Experience (Highly Preferred)

Candidates with prior experience in Collections Analytics will be strongly preferred. Knowledge of collections strategies, delinquency management, customer repayment behaviour, contact optimization, and debt recovery analytics will be a significant advantage.

Experience

- Relevant years of overall experience in Data Science, Advanced Analytics, or Machine Learning.
- Proven experience in building and deploying end-to-end machine learning solutions in production environments.

📌 Data Scientist (Hyderabad)
🏢 Genpact
📍 Hyderabad