Lead Analytics

Job Responsibilities Advanced Model Development & Innovation

• Design sophisticated credit underwriting models using modern ML algorithms (XGBoost, Random Forest, Neural Networks, Ensemble methods)
• Build predictive models leveraging alternative data sources including digital footprints, transactional data, behavioral analytics
• Implement real-time scoring engines and automated decision-making systems
• Develop champion-challenger frameworks for continuous model optimization

Alternative Data Integration & Feature Engineering

• Identify, evaluate, and integrate alternative data sources to enhance model performance
• Build models using psychometric data, device analytics, social network analysis, and open banking data
• Work with unstructured data sources including text, images, and behavioral patterns
• Implement automated feature selection and dimensionality reduction techniques

Machine Learning & AI Implementation

• Apply state-of-the-art ML techniques including deep learning, gradient boosting, and ensemble methods
• Implement explainable AI solutions to ensure model interpretability
• Develop automated machine learning pipelines for model training, validation, and deployment
• Explore and leverage generative AI technologies for innovative underwriting solutions

Team Leadership & Strategic Direction

• Lead and mentor a team of data scientists and analytics professionals
• Take end-to-end ownership of analytics projects from conception to production deployment
• Collaborate with cross-functional teams including product, engineering, and business stakeholders
• Drive analytics strategy and roadmap aligned with business objectives

Model Deployment & Operations

• Implement MLOps practices for streamlined model deployment, monitoring, and maintenance
• Collaborate with data engineering teams to ensure robust data pipelines and infrastructure
• Develop automated model monitoring systems and performance tracking dashboards
• Build A/B testing frameworks for model performance evaluation

Business Impact & Insights

• Analyze large and complex datasets to extract meaningful insights and trends
• Create clear and comprehensive reports, dashboards, and visualizations for stakeholders
• Present findings and recommendations to both technical and non-technical audiences

Required QualificationsExperience & Domain Expertise

• Minimum 10 years in advanced analytics with focus on credit underwriting in BFSI domain
• Proven track record in fintech/digital lending environments developing credit scorecards using modern ML
• Extensive experience with alternative data integration and non-traditional credit scoring methods
• Leadership experience managing teams of data scientists or analytics professionals

Technical Skills & Programming

• Advanced proficiency in Python, R, SQL, and statistical analysis tools
• Expertise in scikit-learn, XGBoost, TensorFlow, PyTorch, and advanced ML libraries
• Experience with big data technologies (Hadoop, Spark) and cloud platforms (AWS, Azure, GCP)
• Proficiency in data visualization tools like Tableau, Power BI, or similar platforms
• Knowledge of MLOps tools (MLflow, Docker, Kubernetes) for model operations

Advanced Analytics Expertise

• Deep expertise in statistical modeling, machine learning algorithms, and predictive analytics
• Strong background in feature engineering, model selection, and hyperparameter optimization
• Experience with NLP techniques for processing unstructured data and text analytics
• Proficiency in experimental design, A/B testing, and causal inference techniques

Alternative Data & Innovation

• Proven experience with alternative data sources (digital, behavioral, psychometric, social media)
• Knowledge of open banking, API integrations, and real-time data processing
• Experience with computer vision, NLP, and unstructured data analysis
• Understanding of data privacy, ethical AI, and responsible lending practices

Leadership & Communication

• Excellent leadership skills with ability to inspire and develop technical teams
• Strong stakeholder management and cross-functional collaboration abilities
• Exceptional communication skills for presenting complex concepts to business audiences
• Self-driven and comfortable working in fast-paced startup environments

Preferred Qualifications

• Advanced degree (B.Tech/M.Tech) in Engineering, Computer Science, Mathematics, or Statistics
• Experience with embedded finance, digital-first lending platforms, or API-based financial services
• Knowledge of microservices architecture and modern software development practices
• Understanding of various lending products and fintech ecosystem dynamics