Head of Data & Analytics

Job Description and Responsibilities:
The Data and Analytics ensures that the franchise unlocks and deploys the power of data in driving growth and revenue and in maintaining the bank’s key competitive advantage.

BAU Responsibilities:
- Collaborate with cross functional partners to identify actionable customer insights and opportunities based on internal and external customer behavior and financial data
- Employ techniques such as statistical modeling and machine learning to enhance customer targeting for acquisition and cross selling, yield optimization, customer experience, improved audit/controls and exceptions handling, increase usage, balance and transaction activity, etc.
- Help manage portfolio profitability by providing financial analytical discipline in portfolio/deepening actions, across the life cycle and across customer journeys.
- Quantify, track and measure the investments and initiatives of the bank and recommend opportunities to enhance and maximize these investments. Further, uncover and explore new milestones, new target market, new engagement model, by quantifying risks and rewards.
- Manage customer communications and offers across the different channels (SMS, eDM, Telesales, Citiphone Inbound, Prelogin, Mobile App, Social Media, etc.). Manage synchronicity and synergy, manage customer fatigue and their channel preferences, manage optimization of delivery of offers to customers (who, how often, which offer, real time/ batch combination, which channel combinations)
- Create opportunities together with business in optimizing and increasing campaigns effectivity and efficiency, improve response rates 2x, 3x through optimization techniques and test and learn capabilities
- Manage resources, organization, talent, upskilling and development for optimal productivity and achievement of business and personal goals, including oversight and maximization of the COE OffShore Analytics and Information Management (AIM) in India, as well as close partnership with Regional Data and Analytics team in Singapore


Governance and Controls:
- Protect data access in Data Warehouse and Enterprise Analytics Platform (EAP) by ensuring access approvals given to DM and non-DM employees, as well as offshore support are fitting and expected within what is allowed by the function and by the bank’s compliance policies on data sharing.
- Overall lead and point of contact for the consumer bank’s data and coordinate with data owners in Business, Technology and Operations to maintain quality data management across the life cycle of the data: from data acquisition, data capture, data maintenance
- Maintain the culture of clean, efficient, ethical and compliant processes in Decision Management, with effective controls to ensure quality of work: accurate, on time, tested and documented.
- Enforce and execute timely all control measures required by the bank such as standard maker-checker process, EUC management, RTC management, CDE and DQIP Scorecards and Model Risk Management (MRM)
- Support and implement initiatives around capturing exceptions and outliers, in data, in processes, in parameter setup, in sales processes, using data

Leading What’s Next / Forward Compatible:
- Drive innovations through out of the box approach to business problems, new statistical techniques, automations and efficiencies in execution, processing and campaigns delivery, campaigns fulfillment.
- Be a thought-leader in emerging digital and data trends in enhancing customer experience and journeys as well as the evolving and increasing consumer expectations
- Lead the upskilling of the team in mindset and in technical skills. Impute design thinking, empathy and insight gathering as foundational in creating a product (campaign, offer, platform, system, etc.) Drive learning and usage of Python, Tableau as new tools and platforms for data mining, model building and visualization
- Migrate and transform old processes from old platforms to new platform investments of the bank to realize speed and scale (EAP for ECM, MRE, EventHub, COPS)
- Lead in developing new use cases for Big Data implementations spanning across different points in the customer journey

Qualifications:
- Bachelors level degree require in Statistics, Economics, Finance, Engineering, or similar quantitative discipline (Graduate level degree preferred)
- 15+ years of working experience in a quantitative field, financial / Credit Card industry preferred
- Solid understanding of the consumer market, customer life cycle, and P&Ls.
- Strong analytical and practical problem solving abilities
- Strong communications (written, verbal presentations and interpersonal) skills, including tact, diplomacy, and ability to influence senior-level executives
- Integrity, maturity, dependability, a positive professional attitude
- Track record of success in delivering high quality work in a fast paced and dynamic environment
- Experience in segmentation, Big Data, modeling, and optimization. Know-how on analytic tools (SAS, R, Python, etc.) and methodologies (regression, CHAID, simulation, etc.). Big data and machine learning experiences are strongly preferred

- Premium Healthcare plan
- Training & development program
- Professional and active working environment

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