What is the opportunity?

CACEIS Malaysia has been a cornerstone of asset servicing since 2008. Strategically located in IOI City, Putrajaya, the company employs over 1,300 skilled professionals, providing a broad spectrum of services to institutional clients across Europe including Custody & Cash Clearing, Fund Administration, Fund Distribution, Master Data Services, Market Solutions, Group Invoicing, Reconciliations and Private Equity & Real Estate Solutions. As a Centre of excellence, CACEIS Malaysia plays a pivotal role in driving the scalability of global operations, enhancing service quality, and implementing standardized processes to meet the diverse needs of its clients. The dedicated team in Malaysia is committed to delivering reliable, high-quality solutions that empower clients to thrive in a dynamic and competitive financial landscape. 

CACEIS Malaysia is building a predictive analytics capability to proactively manage operational errors across its asset servicing activities. This role is the cornerstone of that initiative — a hybrid data professional who will consolidate fragmented, non-standardised operational data, design and maintain structured data pipelines, and develop predictive models that link error patterns to key operational drivers such as team capacity and competency, processing volumes, and platform performance. The successful candidate will transform raw operational data into actionable, forward-looking insights that reduce errors and strengthen operational resilience.

What will you do?

Data Preparation & Management

• Collect, consolidate and prepare operational data from multiple sources.
• Perform data cleansing and validation to ensure data quality and consistency.
• Support the maintenance of structured datasets for reporting and analytics.
• Maintain documentation of data sources and data definitions

Analytics and Predictive Model Support

• Assist in analyzing operational data to identify trends and patterns.
• Support the preparation of datasets for predictive modelling activities.
• Assist in testing, validating and documenting predictive model outputs.
• Perform basic statistical and trend analysis under guidance.

Reporting & Dashboard Development

• Develop and maintain operational reports and dashboards.
• Produce recurring management reports using approved reporting tools.
• Support ad-hoc reporting requests from business stakeholders.
• Highlight trends, anomalies and operational insights

Learning, Collaboration & Continuous Improvement

• Collaborate with Operations, Technology and Business teams to understand data requirements.
• Participate in process improvement and automation initiatives.
• Continuously develop technical knowledge in analytics, data engineering and AI technologies.
• Support documentation of processes and analytical methodologies
  
  

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including performance based bonuses, flexible benefits, and competitive compensation.
• Leaders who support your development through coaching and managing opportunities.
• A world-class training program in financial services.
• A collaborative dynamic culture where personal initiative and hard work are recognized and rewarded.

• Bachelor’s degree in data science, Computer Science, Information Technology, Statistics, Mathematics, Engineering, Finance Analytics or related disciplines.

• Knowledge and practical experience with SQL, Python or Power BI through academic projects is advantageous.

• Relevant certifications (e.g. Microsoft Power BI, Azure Fundamentals, Azure Data Engineer/Data Scientist, Google Data Analytics) are preferred but not mandatory.

• Proven hands-on experience in designing, building, and maintaining data pipelines, dashboards, and analytical solutions.
• Experience applying predictive analytics or statistical modelling to operational, financial, or business process data.
• Track record of working with cross-functional stakeholders (e.g. Operations, Technology, Finance, Risk) to define requirements and deliver data-driven solutions.
• Experience mentoring junior team members or providing technical/analytical guidance is an advantage.
• Solid experience in Python (or similar language) for data analysis, modelling, and automation.
• Experience developing and interpreting predictive models or machine learning solutions in a business context

Skillsets:

• Data Engineering – Advanced
• Predictive Analytics – Proficient
• Data Visualisation – Proficient
• Domain Understanding – Working Knowledge
• Communication – Advanced
• Problem Structuring- Proficient
• Stakeholder Management – Proficient

• Strong analytical and problem-solving skills, with the ability to translate business issues into data-driven solutions.E
• Excellent communication and presentation skills, including the ability to explain complex analytical concepts to non-technical stakeholders.
• High attention to detail and accuracy, with strong ownership of data quality and integrity.
• Demonstrated ability to manage multiple priorities, projects, and stakeholders effectively.
• Proven ability to work both independently and collaboratively, including leading small project teams or workstreams.
• Proactive attitude, continuous improvement mindset, and willingness to challenge existing processes constructively.
• Strong organizational and time management skills, with a focus on delivering outcomes and measurable impact.

• Strong proficiency in SQL and relational databases; experience with data warehousing concepts.
• Advanced proficiency in Microsoft Excel (complex formulas, Pivot Tables,
• Power Query, charts) and strong skills in Power BI or Tableau.
• Strong understanding of data modelling, data cleansing, validation, and governance concepts.
• Good grasp of statistics, including hypothesis testing, correlation, and basic time-series analysis.
• Ability to design intuitive data visualizations and dashboards tailored to business users.