Data Scientist

We are hiring for a Data scientist for one of India's top NBFC. KIndly refer to the details below and apply for the role if your profile is suited. Only apply if you have worked on BFSI projects or belong to a BFSI Company only.

Role: Data Scientist

Location: Chennai (Egmore)

Work mode : Work from office 5 days

Notice period: Upto 60 days

Experience: 1-10 years (Internship experience is not considered)

Mode of Interview : L1 Online Assessment, L2 and L3 Virtual

Data Scientist

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We are seeking a highly skilled Data Scientist with 1-10 years of experience in traditional machine learning model development, advanced statistical analysis, and large-scale data processing. The ideal candidate will be responsible for scaling our analytics capability across the organization and leading analytical initiatives that directly influence product and business strategy. Experience in banking or financial analytics such as fraud detection, credit risk, debt recovery, and cross-sell models is highly desirable.

Responsibilities

• Scale and strengthen the organizations analytical capabilities across all internal functions.
• Drive the development of analytics-led approaches that enhance decision-making and strategic direction.
• Partner with business teams to understand analytical needs and translate them into structured problem statements and analytical solutions.
• Present insights and recommendations to senior leadership in a clear and concise manner, enabling strategic and data-driven decisions.
• Organize, process, and analyze large, diverse datasets from multiple systems and platforms.
• Build reliable, relevant, and efficient reporting structures based on identified business requirements.
• Perform hypothesis testing, A/B testing, segmentation, regression analysis, time series forecasting, and other statistical methods.
• Develop proof-of-concepts (POCs) to validate assumptions and evaluate feasibility of analytical solutions.

Machine Learning Model Development

Build, evaluate, and optimize traditional machine learning models including:

• Logistic Regression ,Decision Trees, Random Forest, XGBoost / LightGBM, SVM, Clustering models, Time series forecasting models, Market basket / association models
• Implement end-to-end model development lifecycle: problem scoping data prep modeling evaluation documentation.
• Validate model performance using AUC, ROC, F1, precision/recall, RMSE, and other relevant metrics.
• Ensure scalable, reproducible, and well-documented model pipelines.

Finance & Banking Use Cases (Mandatory)

• Develop and optimize models for:
• Fraud detection and anomaly detection
• Credit risk scoring and delinquency prediction
• Debt collection and recovery prediction
• Cross-sell / up-sell recommendation models