Joseph Muiruri
Commercial Finance & Data Analyst
Turning complex financial data into faster, sharper commercial decisions
0%
Forecast Accuracy Improvement
0%
Reporting Effort Reduction
0%
Reporting Turnaround Acceleration
Financial Environments I've Worked Across
Good financial analysis should be reproducible, not reheated: if I build a report once, the system should be able to build it again without me.
From reconciling donor funds in rural Kenya to automating commercial dashboards for ASX-listed retail brands in Australia, one throughline stands: turning financial complexity into clarity.
Hello, I'm Joseph Muiruri, a Commercial Finance and Data Analyst with 3+ years of experience across ASX-listed retail, financial consulting and banking environments. My focus is simple: turn raw financial data into forecasts, dashboards and decisions that commercial teams can act on immediately, not weeks later.
- Master of Financial Analysis (Distinction)
- CPA Australia Associate
- B.Com in Finance, JKUAT
Where My Expertise Concentrates
Commercial Finance
- Commercial Finance & Business Partnering
- Budgeting & Forecasting
- Variance & Margin Analysis
Data Engineering
- Power BI Dashboard Development
- SQL & ETL Pipeline Engineering
- Python-Driven Predictive Analytics
Financial Controls
- Financial Modelling & Capital Budgeting
- Financial Reconciliation & Month-End Close
- Audit, Compliance & Regulatory Reporting
Featured Case Studies
Rebuilt Commercial Reporting Infrastructure, Cut Turnaround by 95%
DashboardWorx, a boutique analytics consultancy serving 20+ clients across financial services and commercial sectors, brought me on as Financial Data Analyst Consultant to fix a forecasting process that was fragmented across business units, planned separately in spreadsheets with no shared assumptions or drivers. I traced the breakdown to its structural cause rather than assuming the model needed rebuilding, then designed an integrated revenue and expenditure model built in Excel for transparency and surfaced through Power BI so stakeholders could see the drivers behind the numbers, not just the outputs. I worked the assumptions through directly with finance and operational teams, connected the model to live Power BI dashboards, and produced monthly variance commentary that explained movements rather than reporting them after the fact. Forecast accuracy improved by 40%, and the cost-driver analysis that came out of the variance work identified where discretionary spend was concentrated, informing recommendations that cut it by 10% within four weeks.
40%
Forecast Accuracy
10%
Discretionary Spend Cut
60%
Reporting Effort Cut
95%
Turnaround Acceleration
Classified 7,039 Job Listings by Skill Evidence, Surfacing 1,134 Hidden Data Roles
DataCareer App sourced Australian data-role listings by matching job titles against a keyword list, a method that missed roles like Business Analyst or Reporting Officer that are data jobs in substance, while letting administrative roles with "data" in the title through. As Data Quality & Insights Analyst, I was asked to build a defensible basis for how listings were actually classified. I reframed the question from what a job is called to what skills it requires, building a weighted skill-scoring framework from 34 skill keywords drawn from listing descriptions, each scored by how strongly it signals genuine data work. Applied across an extract of 7,039 listings, the framework surfaced 1,134 hidden data jobs (16.1%) that title-based sourcing had missed entirely, while flagging 1,076 listings (15.3%) as noise. Roughly one in five real data roles had been invisible to the previous method, and the classification became the basis for how the platform now categorises its job database.
7,039
Listings Classified
1,134
Hidden Data Jobs Surfaced
16.1%
of Listings Were Hidden
Built a Loyalty KPI Dashboard for Woolworths Sydney Stores
As part of my data analytics training at The Data Analytics Institute, I built a Power BI KPI dashboard tracking Woolworths Everyday Rewards loyalty performance across Sydney stores. The project required translating raw loyalty and sales data into store-level KPIs that a retail operations team could act on directly. I designed the data model, the KPI logic and the dashboard layout to surface loyalty engagement and trading performance trends by store. The result is a dashboard framework directly applicable to the retail operations and corporate structure roles I am now targeting.
Ways to Work Together
Power BI Dashboard Build
Best for: Retail, FMCG and finance teams without in-house BI capability
Your team is stuck reading static spreadsheets or waiting on ad hoc reports every month-end. I design and build Power BI dashboards, backed by clean SQL data pipelines, that give you live visibility into margin, pricing and trading performance.
Read MoreFinancial Forecasting & Budget Models
Best for: Commercial and finance teams needing a rebuilt forecasting model
Budgeting cycles that rely on last year's spreadsheet rarely hold up under this year's pressure. I build integrated revenue and expenditure forecasting models with variance tracking built in, so your budget-versus-actuals reporting tells you something useful, not just something accurate.
Read MorePredictive Analytics for Finance
Best for: Data-driven organisations ready to move beyond descriptive reporting
Most finance teams have the data to forecast risk and behaviour, but not the modelling skill to use it. I build Python-based predictive models, from credit risk classification to workforce and revenue forecasting, that turn your existing data into a decision-support tool.
Read MoreReady to Talk Numbers?
Book a discovery call or see the engagements behind the metrics.