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Jobs in Singapore   »   Jobs in Singapore   »   Information Technology Job   »   Associate Manager, Data Analyst
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Associate Manager, Data Analyst

Kpmg Services Pte. Ltd.

Within KPMG Singapore, the Information Technology Services (ITS) team is responsible for providing quality IT services and solutions internally to support the business and improve efficiency. You will be part of the Data Office, the department responsible for defining and implementing the Singapore firm’s Data Strategy. The team works with a vision to empower people at KPMG to harness data across the firm to generate actionable insights and drive value.


We’re looking for a resourceful and trustful team player who is passionate about data and technology and has the spirit to diagnose and solve problems within a complex system. As a Data Analyst, your responsibilities would include, but not be limited to:

  • Actively support the execution of the KPMG data strategy implementation
  • Streamlining information from various sources and converting them into the right data structures and/or models that can be analysed as part of a project/application/report to provide greater insights
  • Enable business teams with data access using Power BI and Alteryx. These tools incorporate self-service analytics and empower business teams with data insight autonomy with reduced technical and project costs
  • Work with the Data Architecture and engineering team to define the key pipelines, and data models for data required to support the Business use-cases
  • Support the build of business data assets to advance the scalability and reusability of KPMG data assets
  • Increase adoption of AI/ML use cases across the functions to solve business challenges and drive efficiencies
  • Document processes and guardrails on the usage of data & analytics tools (e.g. Alteryx, Power BI) in the firm
  • Collaborate with Global Data Office to deliver data use cases to meet business & data strategy objectives
  • Lead data literacy & data culture across the firm, support community development; develop training, awareness, and adoption of Data analytics discipline across all functions
  • Be an agent of change and instill data-driven culture across different segments of data users through effective communication and collaboration


Requirement

  • Bachelor’s degree in Computer Science or an equivalent degree in a quantitative discipline with extensive programming experience.
  • At least 4 years of experience in Data analytics in any industry
  • Experience with cloud platform and data technologies such as Azure Data Platform, Azure Machine learning, Azure Databricks, Azure Devops
  • Have working experience in Python for data analysis. Experience with complex analytics and statistical/machine learning techniques using R/Python/Spark.
  • Working experience on Power BI and Alteryx
  • The ability to visualize and understand complex data flows, pipelines, and processes.
  • Good co-ordination and negotiation skills to manage large and diverse sets of stakeholders, with an ability to express complex concepts in clear business terminology


Only shortlisted candidates will be contacted by KPMG Talent Acquisition team, personal data collected will be used for recruitment purposes only.

At KPMG in Singapore we are committed to creating a diverse and inclusive workplace. We believe that diversity of thought, background and experience strengthens relationships and delivers meaningful benefits to our people, our clients and communities. As an equal opportunity employer, all qualified applicants will receive consideration for employment regardless of age, race, gender identity or expression, colour, marital status, religion, sexual orientation, disability, or other non-merit factors. We celebrate the different talents that our people bring and support every staff member in their journey to achieve personal and professional growth. One of the ways we do this is through Take Charge: Flexi-work, our flexible working framework which enables agile and innovative teams to help deliver our business goals.

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