Assistant VP, Data Analyst

Company:
Location: Raffles

*** Mention DataYoshi when applying ***

About UOB

United Overseas Bank Limited (UOB) is a leading bank in Asia with a global network of more than 500 branches and offices in 19 countries and territories in Asia Pacific, Europe and North America. In Asia, we operate through our head office in Singapore and banking subsidiaries in China, Indonesia, Malaysia and Thailand, as well as branches and offices.

Our history spans more than 80 years. Over this time, we have been guided by our values — Honorable, Enterprising, United and Committed. This means we always strive to do what is right, build for the future, work as one team and pursue long-term success. It is how we work, consistently, be it towards the company, our colleagues or our customers.

About the Department

The Technology and Operations function is comprised of five teams of specialists with distinct capabilities: business partnership, technology, operations, risk governance and planning support and services. We work closely together to harness the power of technology to support our physical and digital banking services and operations. This includes developing, centralising and standardising technology systems as well as banking operations in Singapore and overseas branches.

Job Responsibilities

We are looking for an individual with data engineering and analytics experience to join Group Retail Banking and Channels Technology & Operations to help Group Retail Operations organize and wrangle valuable information from big data. The individual should be a self-starter, energetic and have a passion for both problem-solving and telling compelling stories using data. He/she will also work closely with Operation Centers to provide data analytic and insights for transformation initiatives.

  • Design data driven solutions independently to enable Group Retail Operations in identifying process and operational improvement opportunities
  • Design, develop and maintain scalable and flexible data models and pipelines
  • Implement processes and systems to monitor data quality, ensuring production data is always accurate and available for key stakeholders and business processes
  • Ensure regular interaction with key stakeholders to understand their business objectives. Proactively recommend how you think data & analytics could help them achieve their goals.
  • Collaborate with Operation Centers to create, design and push end-user and usage analytics through digital platforms
  • Identify and collect measurements of success of each transformation to prepare and deliver usage/metrics reports to stakeholders with the use of slide presentations, product demonstrations, email newsletters or white papers.

Job Requirements

  • Bachelor’s Degree, preferably in a quantitative field such as Computer Science, Data Analytics, Statistics or Mathematics
  • At least 3 years of hands-on technical experience in data engineering and/or analytics
  • Experience in big data tool (R, Hadoop etc) or data visualization & interactive dashboarding (eg Qlik, Tableau) would be an added advantage
  • Experience in agile approach, actively driving test and learn with data driven insights
  • High attention to details, meticulous and able to work in an ambiguous environment with minimal supervision
  • Proven ability to work creatively and analytically in a problem-solving environment
  • Strong communication / inter-personal skills
  • Assertive in stakeholder’s management
  • Strong understanding of Consumer Banking Products

Be a part of UOB Family

UOB is an equal opportunity employer. UOB does not discriminate on the basis of a candidate's age, race, gender, color, religion, sexual orientation, physical or mental disability, or other non-merit factors. All employment decisions at UOB are based on business needs, job requirements and qualifications. If you require any assistance or accommodations to be made for the recruitment process, please inform us when you submit your online application.

Apply now and make a difference.

*** Mention DataYoshi when applying ***

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