Freelance IT Data Analyst
Budget: ₹100 – ₹400 INR
I manage several fast-growing digital products and need an experienced freelance Data Analyst to turn our raw information into clear, actionable insights. The work sits squarely in the Information Technology space but crosses into marketing and product strategy, so versatility is essential.
What you will tackle
• Receive periodic CSV, JSON, or database exports (mainly MySQL and Postgres)
• Clean and validate each dataset, flagging anomalies or gaps
• Build concise exploratory analyses, then dive deeper with statistical tests or modelling when patterns emerge
• Produce easy-to-read visual dashboards or slide decks that tell the story behind the numbers
Preferred toolset
Python (pandas, NumPy, SciPy), SQL, Excel/Google Sheets, and a modern BI platform such as Tableau, Power BI, or Looker. If you favour R or another stack and can achieve the same clarity, feel free to propose it.
Deliverables
1. Cleaned dataset with documented steps
2. Analytical notebook or script ready for reruns
3. Interactive dashboard or static visual pack (PDF/PPT) presenting key findings
4. One-page executive summary highlighting opportunities and risks
Acceptance criteria
• Reproducible code or workflows, commented and version-controlled
• Visuals load without errors and match described metrics
• Insights are supported by clear statistical evidence or logical reasoning
Most projects are short bursts of 5–15 hours, with the possibility of ongoing collaboration as new data drops arrive. Let me know your relevant experience and favourite analysis win, and we can discuss the first dataset right away.
What you will tackle
• Receive periodic CSV, JSON, or database exports (mainly MySQL and Postgres)
• Clean and validate each dataset, flagging anomalies or gaps
• Build concise exploratory analyses, then dive deeper with statistical tests or modelling when patterns emerge
• Produce easy-to-read visual dashboards or slide decks that tell the story behind the numbers
Preferred toolset
Python (pandas, NumPy, SciPy), SQL, Excel/Google Sheets, and a modern BI platform such as Tableau, Power BI, or Looker. If you favour R or another stack and can achieve the same clarity, feel free to propose it.
Deliverables
1. Cleaned dataset with documented steps
2. Analytical notebook or script ready for reruns
3. Interactive dashboard or static visual pack (PDF/PPT) presenting key findings
4. One-page executive summary highlighting opportunities and risks
Acceptance criteria
• Reproducible code or workflows, commented and version-controlled
• Visuals load without errors and match described metrics
• Insights are supported by clear statistical evidence or logical reasoning
Most projects are short bursts of 5–15 hours, with the possibility of ongoing collaboration as new data drops arrive. Let me know your relevant experience and favourite analysis win, and we can discuss the first dataset right away.