SVP/ED, Team Lead, Data Translator (Private Banking/Wealth), Consumer Banki at DBS Bank

Singapore, Singapore, Singapore -

Full Time

Start Date

Immediate

Expiry Date

22 Aug, 26

Salary

0.0

Posted On

24 May, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Analytics, Machine Learning, Python, SQL, Stakeholder Management, Statistical Analysis, Exploratory Data Analysis, Financial Services, Private Banking, Team Leadership, Data Preprocessing, Feature Engineering, KPI Tracking, Client Portfolio Analytics, Strategic Thinking, Storytelling

Industry

Banking

Description

Business Function As the leading bank in Asia, DBS Consumer Banking Group is in a unique position to help our customers realise their dreams and ambitions. As a market leader in the consumer banking business, DBS has a full spectrum of products and services, including deposits, investments, insurance, mortgages, credit cards and personal loans, to help our customers realise their dreams and aspirations at every life stage. Our financial solutions are not only the best in the business – they were made just right for you. We develop large scale analytical solutions powered by machine learning and AI to drive customer experience, enable product sales and engagement for the Private Banking and Treasure Private Client business. We want to push the boundary on data and AI and create meaningful solutions that can help and assist our customers and differentiate DBS from the competition. Overview This senior role is for a Team Lead in Data Analytics, supporting the Private Bank and Treasures Private Client franchises. It demands a blend of technical proficiency, hands-on involvement, deep business domain knowledge, and exceptional stakeholder management skills. The ideal candidate will excel in complex environments, delivering high-impact analytical and campaign solutions to meet the needs of senior stakeholders. Job Responsibilities Leadership and Team Management Lead the team responsible for Front Office analytics, transforming data into commercial insights and actionable strategies. Oversee hyper-personalized campaign targeting and management (e.g., Next Best Conversation & Next Best Nudges). Lead and manage the full lifecycle of high-impact data and analytics solutions, from conceptualization to implementation, ensuring alignment with business goals and measurable impact. Champion the development of reusable analytical assets and foster knowledge sharing to elevate organizational analytical capabilities and promote continuous learning and technical excellence. Front Office Analytics & Insights Generation RM Productivity Analytics: Drive analysis by reviewing Relationship Manager (RM) activities vs. outcomes (Revenue/NNM achieved), optimizing RM Balanced Scorecards according to business goals, and tracking RM opportunity conversion. Client & Portfolio Analytics: Drive insights relating to attrition risk analysis, pricing and fee sensitivity, client engagement, and client profitability. Exploratory Data Analysis: Lead and personally engage in exploratory data analysis to identify patterns, trends, and anomalies, applying advanced statistical testing and hypothesis validation techniques to ensure insights' reliability. Control Towers & KPI Tracking: Lead the design and implementation of impactful and actionable Control Towers and data compute for KPI tracking and strategic outcome measurement, ensuring continuous visibility into business performance. Client Engagement Management & Effectiveness Oversight: Maintain clear oversight on overall targeting, execution, and measurement of client comms and engagement, ensuring the right message reaches the right client at the right time through the right channel. Effectiveness Measurement: Drive the measurement of campaign effectiveness, building closed-loop attribution from campaign send through to RM/client action, revenue/NNM impact, and client engagement. Stakeholder Engagement & Communication Cross-Functional Collaboration: Collaborate effectively with cross-functional teams and senior stakeholders, including Business Heads, to build strong relationships and ensure a holistic understanding of business needs. Insight Synthesis & Communication: Synthesize complex data insights into compelling, easy-to-understand narratives that enhance executive-level decision-making. Deliver clear, actionable recommendations to senior business leaders, effectively managing expectations. Machine Learning Communication: Interpret advanced machine learning model results and effectively communicate findings to diverse stakeholders, including non-technical audiences, ensuring alignment and shared understanding. Technical Expertise & Innovation Business Domain Knowledge: Leverage deep business banking domain knowledge, preferably in Private or Consumer Banking, to ensure data analytics initiatives are relevant and impactful. Understand key business drivers and objectives, aligning analytics efforts with broader organizational goals. Data Preprocessing: Apply data preprocessing techniques, such as feature engineering, scaling, and normalization, to improve machine learning efficacy together with Data Scientists (experience in this area is advantageous). Continuous Learning: Stay abreast of the latest trends and best practices in data analytics, machine learning, and visualization tools. Proactively identify opportunities to optimize processes and drive innovation, implementing cutting-edge solutions. Job Requirements Master's Degree or Ph.D. in a quantitative field (e.g., Data Science, Statistics, Computer Science). 10-15 years of progressive experience in data analytics or data science, with at least 5 years in a leadership role, preferably within financial services (Private or Consumer Banking). Proven ability to lead and mentor high-performing data analytics teams and manage the full lifecycle of data solutions. Expert-level proficiency in advanced statistical analysis, machine learning techniques, and exploratory data analysis. High proficiency in programming languages (Python, SQL). Exceptional stakeholder management and cross-functional collaboration skills with senior business leaders. Superior communication and storytelling abilities to synthesize complex data into actionable insights for executive-level decision-making. Deep business banking domain knowledge to drive impactful data analytics initiatives. Strong strategic thinking, problem-solving, and continuous learning mindset to foster innovation. Location: DBS Asia Hub Job: Analytics Schedule: Regular Employee Status: Full time DBS is more than a bank — we're shaping the future of finance and communities. With innovation at our core and impact in our DNA, we go beyond banking to build careers, relationships, and a better world. DBS is a leading financial services group in Asia with a presence in 19 markets. Headquartered and listed in Singapore, DBS is in the three key Asian axes of growth: Greater China, Southeast Asia and South Asia. Recognised for its global leadership, DBS has been named “World’s Best Bank” by Global Finance, “World’s Best Bank” by Euromoney and “Global Bank of the Year” by The Banker. The bank is at the forefront of leveraging digital technology to shape the future of banking, having been named “World’s Best Digital Bank” by Euromoney and the world’s “Most Innovative in Digital Banking” by The Banker. In addition, DBS has been accorded the “Safest Bank in Asia” award by Global Finance for 15 consecutive years from 2009 to 2023. DBS provides a full range of services in consumer, SME and corporate banking. As a bank born and bred in Asia, DBS understands the intricacies of doing business in the region’s most dynamic markets and is committed to building lasting relationships with customers. With its extensive network of operations in Asia and emphasis on engaging and empowering its staff, DBS presents exciting career opportunities.

Responsibilities

Lead the Front Office analytics team to transform data into commercial insights and actionable strategies for Private Banking and Treasures Private Client franchises. Oversee the full lifecycle of high-impact data solutions, including hyper-personalized campaign targeting and RM productivity analytics.