Senior Vice President - Analytics & Insights

SBI Card; Gurugram District; On-site; INR 900,000 - 1,500,000; Full time

Job summary

SBI Card is seeking an Analytics Lead to be the enterprise engine for insights, intelligence, and data-driven decision support. The role partners with senior leadership to elevate decision quality and accelerate value creation through analytics-led thinking.

You will build advanced analytical capabilities, oversee predictive models, dashboards, and governance, while leading a high-performing analytics team and driving enterprise-wide measurement of impact.

Qualifications

• Strong analytical and statistical modelling expertise for predictive and prescriptive analytics.
• Proficiency in BI tools and data science platforms; data engineering fundamentals.
• Experience in BFSI, cards, fintech, or consumer lending preferred.
• Exposure to data governance, regulatory expectations, and risk management.
• Excellent stakeholder management and cross-functional leadership.

Responsibilities

• Build and lead enterprise analytics delivering actionable insights across domains.
• Partner with business, finance, risk, and digital teams to inform priorities.
• Oversee development of predictive and prescriptive models (acquisition, attrition, behavior, risk, collections, profitability, CLTV, etc.).
• Drive forecasting, scenario planning, and stress testing models for decision-making.
• Ensure model governance, documentation, versioning, and regulatory compliance.
• Strengthen BI with automated dashboards, real-time reporting, and self-serve analytics.
• Define baselines, KPI targets, and measurement methodologies for initiatives.
• Develop CXO-ready insights packs for reviews and CSO/MD & CEO Office.
• Lead periodic performance reviews with data-driven narratives for progress and gaps.
• Uplift analytics capability across units via coaching and frameworks.

Skills

Predictive analytics

Prescriptive analytics

Segmentation

Forecasting

BI tools

Data science platforms

Data engineering fundamentals

Stakeholder management

Team leadership

Cross-functional collaboration

Education

Bachelor’s degree in Engineering/Statistics/Math/Economics/CS

Tools

Python

R

SQL

Tableau

Power BI

Cloud analytics

Job description

Role Purpose: The Analytics Lead will serve as the enterprise engine for insights, intelligence, and data driven decision support. The role is responsible for building advanced analytical capabilities, enabling strategic choices through evidence-based insights, and strengthening the organization’s ability to measure, predict, and optimise business performance. This position partners closely with senior leadership to elevate decision quality, institutionalize analytics-led thinking, and accelerate enterprise value creation.

Role Accountability:

Enterprise Insights & Strategic Intelligence

• Build and lead the enterprise analytics within to deliver actionable insights across business domains.
• Partner with Business, Finance, Risk, and Digital teams to provide intelligence that informs enterprise priorities, investment decisions, and strategic choices.

Advanced Analytics, Forecasting & Modelling

• Oversee development of predictive and prescriptive models (acquisition, attrition, behavior, risk, collections, profitability, CLTV, etc.).
• Drive forecasting, scenario planning, and stress testing models required for decision-making.
• Ensure robust documentation, versioning, model governance, monitoring, and regulatory compliance.
• Strengthen business intelligence frameworks through automated dashboards, real-time reporting, and self-serve analytics.
• Drive standardization of metrics, characteristics, and performance measures across the organization.
• Build automated insight packs for monthly reviews, committee meetings, and strategic forums.

Value Measurement & Enterprise Performance Tracking

• Design and maintain an enterprise-wide value tracking architecture, linking initiatives to quantified commercial impact.
• Define baselines, benefit estimates, KPI targets, and measurement methodologies for strategic initiatives.
• Lead periodic performance reviews by providing data-driven narratives for progress, gaps, and strategic interventions.

Data Governance, Quality & Cross-Functional Alignment

• Partner with Data Engineering, Technology & Information Security to ensure integrity, accessibility, and governance of data assets.
• Establish data quality standards, lineage documentation, and governance protocols across analytical systems.
• Ensure alignment between analytics, digital journeys, policy changes, customer experience programs, and transformation initiatives.

Leadership, Capability Building & Stakeholder Influence

• Build and lead a high-performing analytics team with expertise in BI, data science, statistical modelling, and business analytics.
• Train and uplift analytical capability across business units through coaching, frameworks, and knowledge-sharing.
• Influence senior leadership through evidence backed narratives and clear recommendations on business priorities.

Enterprise-Grade Storytelling & Senior Management Support

• Develop CXO-ready insights packs, and strategy review documents.
• Craft clear narratives linking data trends to business implications, risks, and strategic pathways.
• Provide pre-reads, scenario views, and deep-dive analyses for the CSO and MD & CEO Office.

Measures of Success

Timely Publishing of Dashboards

• Delivery of monthly function wise dashboards
• Delivery of monthly insight packs, committee dashboards, and strategy review materials as per defined calendar without delays.
• Demonstrated improvement in clarity and actionability of insights as measured through leadership feedback.

Automation through Datalake

• Majority dashboards and reports generated directly from the Datalake, with year on year increase in automation coverage.
• Reduction in manual reporting time by a defined benchmark through end to end datalake ingestion and automated pipelines.

Enterprise Directory of Business Vectors & Metric Definitions

• Creation and maintenance of a centralized, version controlled directory of all business vectors, KPI definitions, and calculation methodologies.
• Periodic update cycle maintained with zero lapse in lineage documentation.

Standardization & Governance of KPIs

• Completion of metric standardization across all functions within agreed timelines
• Zero deviations in calculation logic verified across dashboard builds, business reviews, and MIS packs.
• Achievement of pre defined accuracy thresholds for forecasting and predictive models.
• Monthly monitoring and reporting of model performance with corrective actions implemented within prescribed TAT.

Value Tracking & Commercial Impact Measurement

• Periodic refresh of enterprise value tracking models with fully validated benefit estimates for all initiatives.
• 100 percent alignment between initiative owners and CSO office on value assumptions, baselines, and realized impact.

Data Quality & Governance Enhancements:

• Improvement of key data quality indicators (completeness, consistency, timeliness) as per annual improvement targets.
• Audit ready documentation for models, datasets, and transformation logic with no open compliance gaps.

Enterprise Analytics Capability Uplift:

• Completion of planned analytics capability building programs with measurable improvement in business team proficiency.
• Strengthened internal analytics community demonstrated through increased self serve usage and reduction in ad hoc request load.

Technical Skills / Experience / Certifications

• Strong analytical and statistical modelling expertise (predictive/prescriptive analytics, segmentation, forecasting).
• Proficiency in BI tools, data science platforms, and data engineering fundamentals.
• Ability to synthesize insights from complex datasets and articulate clear business recommendations.
• Experience in BFSI, cards, fintech, or consumer lending preferred.
• Exposure to regulatory expectations around data, model governance, and risk management.
• Strong stakeholder management, team leadership, and cross-functional collaboration experience.

Qualification

• Bachelor’s degree in Engineering, Statistics, Mathematics, Economics, Computer Science, or related quantitative discipline.
• Certifications in analytics, data science, or BI tools (e.g., Python, R, SQL, Tableau, Power BI, cloud analytics) will be an advantage.