Rubansi Vincent — Data Analyst

RV

About me

I don't just build dashboards — I sit with your business until the numbers make sense, then hand you something your team can run with.

Over six years I've worked across e-commerce, fintech, and operations, wrangling data with SQL and Python, modeling in Power Pivot, and turning it all into dashboards in Power BI. I'm also a CPA-trained analyst — I read a balance sheet as fluently as a dashboard, so financial statements, ratios, and FP&A aren't a translation layer for me. My happy place is the messy middle: where exports don't match, definitions disagree, and nobody trusts the report.

I work best with founders and small teams who need answers, not a 40-page deck. Clear questions in, confident decisions out.

Clear Decisions Concise reports Fast turnarounds

Skills & tools

A full analytics stack, end to end.

From the first query to the final dashboard — here's where I spend my time and what I reach for.

Languages & querying

SQLPostgres · BigQueryExpert
Pythonpandas · numpyAdvanced

BI & modeling

Power BIdashboards · data vizExpert
Excelmodeling · automationExpert
Power PivotDAX · data modelsAdvanced
Power QueryETL · transformsAdvanced

Engineering & cloud

Git & GitHubversioning · reposAdvanced
DatabricksSpark · Delta LakeWorking

How the stack fits together

A typical engagement, tool by tool.

SQL

Extract & join raw source tables

Collect

DBx

Databricks

Spark & Delta Lake at scale

Process

PQ

Power Query

Clean, reshape & automate refresh

Transform

Py

Python

Stats, forecasting & heavy lifting

Analyze

PP

Power Pivot

Data models & DAX measures

Model

XL

Excel

Modeling, automation & ad-hoc analysis

Build

BI

Power BI

Ship it as a living, interactive dashboard

Deliver

Git

Git & GitHub

Version & collaborate across it all

Version

From the editor

A real working session — pulling raw rows straight from a sales warehouse in PostgreSQL: a quick SELECT * across the orders fact table, joined to regions and filtered to the latest period.

monthly_sales.sql cohorts.sql +

sales_warehouse · postgres

-- Browse recent orders in the sales fact table
SELECT *
FROM sales.orders    o
JOIN sales.regions   r USING (region_id)
WHERE o.order_date >= '2025-01-01'
  AND r.region_name IN ('EMEA', 'APAC')
ORDER BY o.order_date DESC
LIMIT 250;

▶ Query returned 250 rows 0.018s · 2,418,663 rows scanned

order_idorder_dateregionqtyunit_priceline_total

ORD-482172025-05-31EMEA3129.00387.00

ORD-482052025-05-31APAC1412.50412.50

ORD-481982025-05-30EMEA288.00176.00

ORD-481862025-05-30APAC564.20321.00

ORD-481712025-05-29EMEA1540.00540.00

ORD-481602025-05-29APAC497.50390.00

ORD-481492025-05-28EMEA2215.00430.00

Services

Ways I can help your team.

Pick the piece you need, or bring me a messy problem and I'll tell you where to start. Every engagement is scoped with a clear deliverable and a flat quote.

01

Data Cleaning & Prep

Reconcile scattered, conflicting exports into one trustworthy dataset everyone agrees on — the foundation for everything else.

SQLPower Query

02

Data Modeling

Robust data models and reusable DAX measures that stay accurate and fast as your data — and your questions — grow.

Power PivotExcel

03

Insight & Analysis

Segmentation, forecasting, and A/B testing that move past "what happened" to the answer you can actually act on.

PythonSQL

04

Dashboards & Reporting

Interactive Power BI dashboards your whole team actually checks — the right metrics, no clutter, refreshed automatically.

Power BIPower Pivot

05

Data Pipelines & ETL

End-to-end ETL/ELT and medallion architectures so your data flows reliably from source to decision.

ETL / ELTPower Query

06

Financial Planning

Budgets, rolling forecasts, and variance analysis — the models that show leadership where the business is heading and why actuals drifted from plan.

ExcelPower BI

07

Financial Analysis

Balance-sheet, liquidity and solvency analysis with ratio and working-capital trends — reading the three statements to gauge the real financial health of the business.

Ratio AnalysisExcel

08

Financial Reporting

Financial reporting, P&L, cash-flow and balance-sheet reporting, plus project reports and audit-ready datasets that turn the month-end close into a decision tool.

Power BIDAX

09

Profitability & Cost Analysis

Margin, unit-economics, and cost-driver analysis — pinpointing which products, customers, or channels make money and where to cut or invest.

SQLPython

Sectors & industries

Domains I've worked across.

Data problems rhyme from one industry to the next — but the context matters. Here's where I've learned the vocabulary, the metrics, and the edge cases.

Retail Inventory turns, basket analysis & demand forecasting

↗

E-Commerce Funnel, cohort & conversion-rate analytics

↗

Financial Services Financial reporting, FP&A & risk dashboards

↗

Healthcare Patient flow, claims & outcomes reporting

↗

Manufacturing Production yield, OEE & cost-driver analysis

↗

Hospitality Occupancy, RevPAR & guest-spend insights

↗

6 industries · from raw data to decisions

Featured work

Case studies, not screenshots.

Every project below is a real problem, a clear approach, and a measurable result. Swap in your own brief and let's write the next one.

CASE 01

Subscription revenue, finally trusted.

SQLPythonPower PivotPower BIForecasting

The problem

A SaaS founder had three "revenue" numbers from three tools — none agreed. Board reporting was a guess.

What I did

Built one source of truth in SQL, reconciled billing vs. ledger in Python, and modeled a trailing forecast in Power Pivot the whole team could refresh in one click.

+38%

net revenue clarity

1 click

board-ready refresh

Net revenue · trailing 12 mo

ActualForecast

CASE 02

Cutting a 3-day report to 30 minutes.

Power QueryExcelAutomation

The problem

An ops team rebuilt the same weekly inventory report by hand — copy, paste, pivot, repeat. Three days, every week.

What I did

Rebuilt the pipeline in Power Query with automated refresh and validation, so the report regenerates itself and flags anomalies before anyone opens it.

94%

time saved weekly

312hrs

recovered per year

Hours per weekly report

ManualAutomated

W1

W2

W3

W4

W5

W6

CASE 03

Finding the 20% of customers driving 80% of churn.

PythonSQLSegmentationPower BI

The problem

A subscription brand was losing customers but couldn't say which kind — or why — so retention spend was scattershot.

What I did

Segmented the base with Python clustering, surfaced the at-risk cohort, and shipped a live Power BI dashboard so the team could watch the segments shift week to week.

−31%

churn in 2 quarters

4 segments

now tracked live

Churn by customer segment

At-risk power users52%

Price-sensitive23%

Low engagement15%

Other10%

How I work

Five steps from question to confidence.

No black boxes. You'll always know where we are and what comes next.

01

Frame

We pin down the real question — and how you'll know when it's answered.

02

Collect

I pull and join your sources in SQL, however scattered they are.

03

Clean

Power Query & Python to reconcile, validate, and make it trustworthy.

04

Analyze

Models, segments, and tests that turn the data into an actual answer.

05

Deliver

A dashboard or report your team will keep using long after I'm gone.

Background

Education & certifications.

Education

LB

Senior Data Analyst Bootcamp

Luke Barousse · Excel, Power BI & Python for Data Analysts

2025

ALX

Data Analytics Bootcamp

ALX · Power Query, Power Pivot, SQL, Power BI & Python

2025

SAA

AWS Solutions Architect Associate

AWS · EC2, VPC, Redshift, Athena, RDS, S3, Lambda

2025

AWS

AWS Cloud Computing

AWS · Cloud Computing Essentials

2025

CPA

Certified Public Accountant (CPA-K)

KASNEB · Financial Analytics & Reporting

2013 — 2016

Certifications

LB

Senior Data Analyst Bootcamp

Luke Barousse · Cert 1 ↗ Cert 2 ↗

2025

ALX

Data Analytics Bootcamp

ALX · Certificate of Completion

2025 ↗

AWS

AWS Cloud Computing

AWS · Cloud Computing Essentials

2025 ↗

SAA

AWS Solutions Architect Associate

AWS · EC2, VPC, Redshift, Athena, S3, Lambda

2025 ↗

CPA

Certified Public Accountant

KASNEB · CPA-K

2016

Kind words

What clients say.

★★★★★

"

Rubansi took a tangle of spreadsheets nobody trusted and turned it into the one report our board actually opens. The forecast has been scary accurate.

Founder

SaaS startup

★★★★★

"

We went from dreading the weekly report to never thinking about it. It just shows up, correct, every Monday. Easily the best ROI we've had on a contractor.

Operations Lead

E-commerce brand

★★★★★

"

Clear communicator, fast, and genuinely curious about the business. He found a churn pattern we'd been missing for a year — in his first week.

Head of Growth

Subscription company

Contact