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Data analysis services for startups and growing businesses
I'm Muhammad Zubair, a freelance data analyst based in Pakistan and working with clients worldwide. If your data sits in spreadsheets, a database or exports from several tools, and you need a clear, defensible answer from it, that is the work I do.
What this covers
Cleaning and preparation
Fast, reproducible data wrangling and feature engineering. Messy exports are turned into a dataset you can trust.
SQL at the source
Querying, joining and shaping data at the source, before it reaches a dashboard.
Exploration and statistics
Hypothesis tests, distributions and uncertainty — so conclusions hold up.
Reporting you can reuse
Charts and summaries written for the people who will act on them, with Excel handoffs where that is how your team works.
Questions this work answers
- Where does revenue or margin actually come from, and where is it leaking?
- Which customers are leaving, and what do they have in common?
- Which products, channels or campaigns are worth more investment?
- Is a change in a number real, or just noise?
Tools
- Python
- SQL
- Pandas
- Excel
- Jupyter
- Statistics
Related case studies
These are public projects with code on GitHub. Seven of my nine case studies use synthetic data generated for the project, so they show method and engineering rather than client results. Each README states its data source and limitations.
- E-commerce Growth & Profitability Analytics. End-to-end case study across customers, products, marketing and returns — cleaning, KPI modelling and exploratory analysis. Tools: Python, Jupyter, Pandas, SQL.
- SaaS Churn, Retention & Revenue-Risk Analytics (built on synthetic data generated for the project). SQL + Python pipeline with machine-learning churn models, probability calibration and causal uplift analysis on subscription, usage and revenue data. Tools: Python, SQL, ML, Calibration, Uplift.
- B2B Sales Pipeline & Revenue Intelligence (built on synthetic data generated for the project). Lead scoring with calibrated ML, revenue forecasting, sales-capacity optimisation and next-best-action logic. Tools: Python, ML, Forecasting, Optimization.
See all repositories on GitHub
How a project usually runs
- Agree the question. We settle what decision the work should support and what a useful answer looks like.
- Look at the data. I review what you have, check its quality, and tell you early about any limits.
- Build and check. I do the analysis or build the model, and test it before presenting it.
- Hand over. You receive the results in a form your team can use, with the reasoning written down.
Common questions
What do you need from me to start?
A description of the decision you are trying to make, and access to the data or an extract of it. A spreadsheet export is fine.
How much does a data analysis project cost?
It depends on the size of the data and the question. Send me the details and I will reply with a clear scope and quote rather than a generic price list.
Do you work with clients outside Pakistan?
Yes. I work with clients worldwide and communicate in English by email, Upwork or Fiverr.
Which tools do you use?
Mainly Python (with Pandas) and SQL for the analysis, and Excel, Power BI or Tableau for the reporting layer, depending on what your team already uses.
Related services: Dashboards · Predictive analytics
Further reading
Tell me what you are trying to decide
Send a short description of your data and the question behind it. I will reply personally with whether I can help and what the next step would be.
Email hello@zubairlabs.com Use the project form Hire on Upwork