Chapter:
Data science & analytics
Mission statement
The Data Science and Analytics chapter aims to apply novel quantitative and algorithmic approaches to solve business problems. We leverage our capabilities in analytics, machine learning and modelling, along with the commercial and industry expertise across the wider firm to deliver insights and solutions that are tailored and meaningful, while maintaining a high standard of ethical data practice.
We strive to be a trusted analytics partner in our clients’ digital maturity journey and work alongside them in an agile and iterative way to ensure that our approaches and solutions are aligned to their interests and long-term success.
What we do
The Data Science and Analytics chapter offers a range of services to support our clients in better, data-driven decision making.
The services we offer include:
01 Data visualisation and reporting:
We can help you create reporting metrics, compelling visualisations, and reports that convey insights in a clear and actionable manner, allowing you to focus on the decisions that matter to you.
02 Modelling:
Our team has extensive experience in predictive modelling and optimisation. We can support you with predictive model builds to forecast future trends or identify opportunities and risks using statistical analysis and machine learning, or optimise complex systems and decisions using mathematical models and simulation.
03 Data mining and pattern recognition:
We can help you process and mine large datasets, helping you to uncover hidden relationships and features that could allow you to identify new opportunities or risks. This can include clustering and segmentation, anomaly detection and rule mining.
04 Model validation:
Our experience in model building and modelling leading practices can also be utilised to provide you with the comfort that models built within your organisation are built-to-spec and fit-for-purpose. Our model review capabilities cover the breadth of the modelling pipeline including ETL processes and pipelines, bespoke code and logic, model training and evaluation, and governance practices.
05 Data strategy development:
If your organisation is still in the process of building its data practice, or you have recently decided to revamp its data and analytics function, we can help you develop a data strategy that aligns your organisational objectives with your data ambitions, and advise you on all aspects of data and model governance and management.
Success stories
Meet the
chapter leads
Tim Wipiiti-Benseman
Data Science Chapter Co-Lead
Tim is a highly competent analyst/developer with extensive experience in Business Intelligence, Data Engineering & Warehousing, Data Architecture, Transformation & process efficiency and Data Visualisation & Story Telling. With strong consulting & communication skills Tim can bridge the gap between business and technology turning customer visions into tangible solutions.
Martin Ooi
Data Science Chapter Co-Lead
Martin joined KPMG Lighthouse in and is focused on delivering data science and analytical solutions with an emphasis on machine learning, modelling, and business intelligence. He has worked with clients across a range of industries on various problems ranging from financial and demand forecasting, churn prediction, segmentation, and computer vision.
Want to be a part of the team?
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