Senior Data Scientist

Job Title: Senior Data Scientist Company: Paramount Hr Job Category: Data Science Roles & Responsibilities: Job Summary Own end\-to\-end development of credit scorecards and decision analytics across bureau, platform, behavioural and portfolio data \- from population and target definition through deployment and monitoring. Key Responsibilities * Define development populations, observation/performance windows and targets using portfolio maturity, vintage, roll\-rate and business context; benchmark existing scores before recommending a new model or recalibration. * Clean and profile data, engineer interpretable features, prevent leakage and build explainable benchmark and challenger models across bureau, platform, repayment and other approved data. * Complete champion\-challenger selection and validation using KS, Gini/AUC, calibration, stability/PSI, out\-of\-time and segment performance; create score scaling, grades, reasons, limitations and model documentation. * Translate selected models into policy/BRE treatment, approval/referral/rejection, limit, pricing and tenure logic; prepare deployment artefacts, golden cases, API/UAT evidence and production\-monitoring requirements. * Develop EWS, collections, fraud/trust, propensity and portfolio analytics, and selectively support grounded NLP/LLM use cases such as document extraction, evidence retrieval and internal risk summaries. Core Competencies * Strong statistical discipline combined with practical credit judgement \- able to distinguish predictive lift from leakage, instability or weak business meaning. * Hands\-on ownership mindset: comfortable coding, challenging data, presenting decisions and following models through production monitoring. * Clear communicator who can explain model behaviour, limitations and business impact to Credit, Underwriting, Technology, management and assurance teams. * Understanding of detailed data statistics methods like regression, time series, sampling theory, hypothesis testing etc. Must\-Have Requirements * 5\-8 years of hands\-on Data Science / statistical modelling experience, including at least 3 years in lending, credit risk, underwriting or closely related BFSI analytics; strong Python and SQL are mandatory. * Personally built at least one credit scorecard or underwriting model end\-to\-end, including population/target design, feature engineering, validation, calibration, deployment support and monitoring. * Strong understanding of bureau and lending data, model governance, explainability, reason codes and production implementation through policy/BRE, APIs or decision engines. * Exposure to logistic scorecards and ML methods such as XGBoost/CatBoost/LightGBM, along with cloud, MLflow, APIs, Git and MLOps practices. * B.E./B.Tech/B.Stat Ideal Candidate Profile * A credit modeller first: technically strong, commercially aware and able to translate statistics into defensible lending treatment. * Has worked with imperfect real\-world data and can make transparent decisions on exclusions, missingness, stability, segments and implementation trade\-offs. * Uses Applied AI selectively where it improves analysis or productivity, without over\-engineering the role or weakening model and policy governance. Work Location: Mumbai, India Availability: Full time

Good\-to\-Have (Optional) * Experience in MSME, embedded finance, line\-of\-credit, working\-capital, collections, fraud or early\-warning analytics. * Practical exposure to NLP/LLM, RAG or document\-intelligence use cases with grounding, evaluation, privacy controls and mandatory human review. Key Skills: Data Science, Python, SQL, Statistics Salary: Not disclosed