“We've grown to the point where gut feel isn't enough — but we don't have anyone dedicated to data yet.”
Work out the three or four numbers that actually run the business, and build the simplest version that gets them in front of the right people reliably.
“We've got dashboards, a bit of analysis, some ad hoc reports — I just don't know if we're pointed at the right things.”
Map what exists against what the business actually needs to decide, then set a short plan for what to build, fix, or drop.
“The systems work fine. What I need is someone to help me understand why customers aren't coming back.”
Dig into the data you already have to find the actual drivers, rather than proposing infrastructure you don't need.
“Finance and sales each have their own version of revenue, and I can't tell which one to trust.”
Trace both numbers back to source, find where they diverge, and agree on one definition everyone uses going forward.
“Closing the month eats half of the next one, and by the time the numbers land we've already moved on.”
Find where the time actually goes, and take the parts that don't need a person out of the loop.
“The one person who understood our data left, and I'm not sure what's still working correctly.”
Find out what's actually still running, document it, and make sure it doesn't depend on one person again.
I've spent over a decade in data and analytics — including rebuilding Trust Bank's reporting pipelines on my own, turning reports that took two weeks to compile by hand into ones that updated automatically by the next morning. Previously at Trust Bank Singapore, Shopify, National University Health System (NUHS), and Wego.com.
Singapore's role as a regional hub gives clients across the region practical, day-to-day advantages — not just a postal address.
Familiar business practices, strong infrastructure, and straightforward cross-border contracting.
GMT+8 means real-time collaboration across Asian business hours — no overnight waits.
Engagements contracted under Singapore law with SGD invoicing — a framework most regional businesses are comfortable with.
10+ years across finance, technology, healthcare, and e-commerce — applied to your specific context.
For many growing companies, data work doesn't fit the full-time hire model — yet. You need experienced expertise for strategy, hands-on support for execution, and flexibility as priorities shift. For established teams, the need is often different: temporary cover, a focused project, or a senior hand to spin up a new regional capability quickly.
Dashboards, automation, and analyses that drive faster decisions — done properly, with no shortcuts that create technical debt.
Whether it's a 4-week sprint or an ongoing partnership, the work is built to last — not patched together to look impressive.
Fractional partnerships for teams building data capabilities from the ground up. Project-based work for established teams with a defined scope and deadline. Interim coverage for hiring gaps or new regional teams.
Start with immediate improvements while building foundations.
Create solutions based on proven impact and your specific context.
Build your team's capabilities with documentation and knowledge sharing.
Clear pricing for growing teams — no hidden costs, no surprises. Project and interim work quoted separately.
Everything you need to start using data to grow your business.
Strategic guidance without full partnership commitment.
Ongoing data work that adapts to your monthly priorities — strategy, dashboards, analyses, and execution. Less than the cost of a junior analyst hire.
Higher-capacity ongoing partnership for teams running multiple initiatives concurrently.
Defined-scope projects, interim cover, or larger engagements with custom requirements. Quoted on context — let's discuss your scope.
Discuss scope →Infrastructure costs (cloud hosting, databases, visualization tools) are billed directly by providers — typically minimal for small setups, S$200–800/month for cloud-based systems as you scale. I guide you toward cost-effective options and manage setup.
I'd rather tell you up front than discover it three months in.
Moving from manual to automated workflows, basic to sophisticated analytics, or building new capabilities while maintaining existing ones.
Strategic architecture decisions, guidance for growing capabilities, or temporary senior coverage during transitions or hiring gaps.
Establishing proper data practices from the start — avoiding the common pitfalls and technical debt of retrofitting later.
Backlogged projects, limited capacity, or new opportunities you can't address without deprioritising existing work.
Specialised fields like genomics, quantitative trading, or advanced ML research that require deep domain knowledge beyond general data capabilities.
Very deep, specialised work that requires dedicated senior expertise 100% of the time fits better with a full-time hire than a fractional model.
A fully internal team handling all data work without external support is a valid approach — though it requires significant hiring investment and time.
Quick to engage and polished delivery. But the highest cost, and rotating teams can mean re-explaining your business.
Builds deep business knowledge over time. But slow to hire, and the highest-commitment option.
Fast to start, easy to adjust. The same person learns your business, at a fraction of the cost of alternatives. Lighter-touch options from S$900/month.
Full-Time Hire: Approximate estimate including base salary, employer CPF, and typical benefits. Actual costs vary by experience level, industry, and role scope. Excludes recruitment and onboarding.
Traditional Consultancy: Approximate estimate based on observed rates for engagements of comparable scope. Pricing varies significantly by firm, engagement type, and duration.
I'm based in Singapore, and working with companies outside Singapore is straightforward under Singapore's business and legal framework — here's how the practical details work.
Have a question I haven't covered? Book a discovery call or send me a WhatsApp message — I'm happy to discuss your specific situation.
Let's discuss your data challenges in a 30-minute call and see if I'm a good fit. No pressure, no hard sell.
