Senior Vice President – Operations Analytics

Job description

**Senior Vice President – Operations Analytics (C14)** **Function:** Analytics & Information Management (AIM) – Operations Analytics **Location:** Bangalore, India **People Management:** Yes (20+ team members) **Travel:** Up to 10% **Role Overview** The **Senior Vice President – Operations Analytics** is a senior leadership role responsible for driving **analytics‑led and AI‑enabled decision support** across Global Operations. The role partners closely with Operations and Business leadership to improve **cost efficiency, customer experience, operational productivity, and risk management** through advanced analytics. This position requires a leader who can operate at scale—setting analytics strategy, translating complex operational problems into data‑driven solutions, influencing senior stakeholders, and building **forward‑compatible analytics talent and capabilities** to meet the evolving needs of the organization. The SVP is accountable for both **business impact and capability maturity**, ensuring analytics and AI are embedded into how Operations makes decisions. **Key Responsibilities** **Operations Analytics Strategy & Leadership** - Define and execute the **Operations Analytics strategy**, aligned with business objectives, customer outcomes, and risk priorities. - Act as a trusted analytics advisor to senior Operations leadership, influencing decision‑making through data‑driven insights. - Identify and prioritize high‑impact opportunities where analytics and AI can deliver measurable improvements in operational performance. **Advanced Analytics & Insight Generation** - Lead development of advanced analytics solutions addressing core Operations challenges, including: - Cost reduction and efficiency improvement - Productivity, capacity, and demand optimization - Customer experience enhancement - Operational risk identification and mitigation - Translate ambiguous business problems into structured analytical approaches and **repeatable solution frameworks**. - Ensure insights are actionable, commercially grounded, and clearly linked to business outcomes. **AI Adoption & Innovation** - Drive the **responsible adoption of AI, machine learning, and advanced analytical techniques** within Operations Analytics. - Partner with stakeholders to move AI from experimentation to **scaled, embedded usage** in operational decision‑making. - Champion explainable, ethical, and risk‑aware use of AI in analytics solutions. - Stay abreast of emerging analytics and AI trends to ensure the function remains future‑ready and relevant. **Business Partnership & Stakeholder Management** - Build and maintain strong relationships with senior stakeholders across Operations and Business teams globally. - Independently manage complex stakeholder engagements—from problem framing to insight delivery and execution tracking. - Influence cross‑functional teams to adopt analytics‑ and AI‑driven decision practices. **Execution & Delivery Management** - Own end‑to‑end analytics delivery across a multi‑layered team in a highly matrixed environment. - Ensure consistent standards of quality, timeliness, and business impact across all analytics initiatives. - Balance short‑term execution priorities with long‑term strategic capability building. **Talent, Capability & Culture Building** - Build and sustain a **forward‑compatible Operations Analytics organization** with strengths in: - Advanced analytics and problem solving - AI / ML and emerging analytical techniques - Deep operations and business domain expertise - Lead and manage teams of **20+ analytics professionals**, including people managers. - Attract, develop, and retain top analytics talent; build leadership depth and succession readiness. - Mentor leaders and teams to strengthen analytical rigor, business acumen, and executive storytelling. - Foster a high‑performance culture centered on ownership, innovation, continuous learning, and ethical judgment. **Risk, Governance & Control** - Ensure analytics and AI solutions appropriately consider operational risk, regulatory expectations, and control requirements. - Partner with risk and control teams to support safe, compliant, and transparent analytics‑led decision‑making. - Escalate and manage risks and control issues responsibly, with a strong focus on the firm’s reputation and client outcomes. **Required Experience & Skills** **Experience** - **15+ years** of overall experience, with **10+ years in analytics roles**, preferably supporting Operations. - **6+ years** of experience leading analytics teams in complex, matrixed organizations. - Strong background in **financial services / consumer banking operations**. - Proven track record of delivering measurable business impact through analytics. - Deep understanding of **operational metrics, cost drivers, customer journeys, and operational risk indicators**. **Analytics & Problem‑Solving Skills** - Expertise in operations analytics, performance optimization, and structured problem solving. - Ability to synthesize large, complex datasets into clear insights that drive action. - Experience designing scalable and repeatable analytical frameworks. - Familiarity with advanced analytics techniques, including predictive modeling and AI/ML concepts. **Leadership & Behavioral Competencies** - Strong strategic mindset with a bias for execution and results. - Executive presence with exceptional communication and stakeholder‑influencing skills. - Ability to lead through ambiguity and operate effectively in fast‑paced environments. - High level of ownership, accountability, and commercial judgment. **Education** - **Required:** Bachelor’s degree in a quantitative or analytical discipline (Engineering, Statistics, Mathematics, Economics, Computer Applications, Information Systems). - **Preferred:** MBA or Master’s degree in Analytics, Economics, Operations Research, Management Science, or related fields from a premier institute. **What