Analytics Team Lead

About the Company:Our passion at EXL is enabling organizations to achieve a measurable, competitive advantage through Data Management. We partner with our clients to design and implement scalable, accessible, and innovative solutions. Our goal is to make sense of data to drive client’s business forward through data strategy, data governance and building cloud data platforms. EXL is a leading data analytics and digital operations and solutions company that partners with clients to improve business outcomes and unlock growth. By bringing together deep domain expertise with robust data, powerful analytics, cloud, artificial intelligence (“AI”) and machine learning (“ML”), we create agile, scalable solutions and execute complex operations for the world’s leading corporations in industries including insurance, healthcare, banking and financial services, media, and retail, among others. Focused on driving faster decision-making and transforming operating models, EXL was founded on the core values of innovation, collaboration, excellence, integrity and respect. Headquartered in New York, our team is over 44,500+ strong, with more than 50 offices spanning six continents.About the Role:EXL’s Advanced Analytics Practice works with leading banks, fintechs, and financial institutions to design, build, and implement cutting-edge predictive models and data-driven strategies across the customer lifecycle. We are seeking an Analytics Model Development lead to drive the end-to-end development, execution, and monitoring of predictive models—spanning across areas such as acquisition, response, churn, underwriting—while managing existing client relationships and identifying new business opportunities. This role requires deep statistical expertise, advanced data science capabilities, and strong business acumen to translate data-driven insights into effective models that balance growth, profitability, and risk mitigation. Additionally, it requires strong consultative and relationship-building skills with the ability to influence senior stakeholders and bridge the gap between technical data science and business strategy.Key Responsibilities:End-to-End Model Development & Innovation: Lead the design, development, and validation of predictive models across the banking lifecycle, which may inclUde: Risk/Decision Models: Credit scoring, underwriting frameworks, behavior modeling, collection/loss mitigation, and fraud detectMarketing/Growth Models: Propensity/response modeling, customer segmentation, attrition/churn forecasting, Next-Best-Action, and Customer Lifetime Value (LTV).Perform detailed portfolio analysis using internal customer transactional data, bureau attributes, digital footprints, and alternative data sources to optimize business decisionDrive innovation by leveraging advanced statistical techniques, machine learning algorithms (e.g., XGBoost, Random Forests, Neural Networks), and automation to strengthen the client's analytical capabilityStrategy, Governance & Stakeholder CollaborationDeliver interactive MIS reports, performance dashboards, and model reviews to monitor model health, track population stability (PSI), assess characteristic drift (CSI), and evaluate ROI/strategy effectivenessCollaborate with client stakeholders and cross-functional teams (Product, Risk, Marketing, Finance, Compliance, and Technology) to align modeling frameworks with core business objectivesEnsure strict adherence to regulatory and governance requirements, including Model Risk Management (MRM) guidelines (e.g., SR 11-7), consumer privacy laws, and fair lending practicesProvide clear insights and strategic recommendations to senior leadership on model performance, emerging trends, and forward-looking data strategiesAccount Management & Business DevelopmentBuild and nurture long-term client relationships by understanding their core analytical pain points and positioning EXL’s modeling solutions effectively.Identify opportunities to expand engagements through the cross-sell/up-sell of advanced analytics, data engineering, model validation, and strategy consulting servicesPartner with business development teams to support proposal creation (RFPs), client pitches, and the definition of value-driven project outcomesQualification:Education: Bachelor’s degree in Statistics, Mathematics, Data Science, Economics, Operations Research, Engineering, or a highly quantitative field.Experience: 7+ years of experience in predictive modeling, model development, or data science within management consulting, banking, or financial services.Domain Expertise: Strong understanding of retail banking and consumer lending products (credit cards, personal loans, mortgages, auto loans) and their lifecycle dynamics.Advanced proficiency in Python, R, SQL, or SAS for data manipulation and statistical modeling.Strong hands-on experience with regression, classification, clustering, time-series forecasting, and machine learning frameworks.Familiarity with data visualization tools like Tableau or Power BI is a plus.Communication & Collaboration: Excellent communication and presentation skills, with a proven ability to translate complex data science concepts into actionable business strategies for executive stakeholders.Regulatory Knowledge: Solid understanding of model risk management frameworks (e.g., SR 11-7), compliance standards, and data governance in a regulated banking environmentClient & Growth Mindset: Proven experience managing client relationships and contributing to business development efforts, proposal writing, or solution architecture.Benefits:Medical insurance, Vision insurance, Dental insurance, 401(k), Paid maternity leave, Paid paternity leave