MIS & Data Systems Lead (Full Stack Developer / Data Scientist)

MIS & Data Systems Lead (Full Stack Developer / Data Scientist)

Company:

Location:

Reports to:

Experience:

About Purv Group

Purv Group is a diversified conglomerate with a Pan India presence, operating dynamic subsidiaries across industries such as flexible packaging materials trading, beverage packaging manufacturing, recycling, education, and agriculture. With over 25 years of rich history, we are dedicated to excellence, innovation, and sustainability.

Role Summary

Own our “single source of truth” and build from scratch: data pipelines, lean internal apps, and decision-grade dashboards across production, commercial, and finance—without creating a large team. Be the doer-in-chief who scales impact through smart tooling, not headcount.

What You’ll Do

• Own the data stack:

  Design and maintain pipelines (Tally/ERP/MIS/Sheets ➜ warehouse) with auditable, fresh data.

• Apps & automation:

  Lightweight tools for production planning, approvals, data entries, alerts/WhatsApp bots.

• Dashboards & UX:

  :

  Design fast, intuitive BI dashboards (OEE, scrap, energy/kg, OTIF, SKU profitability, WC days) with thoughtful UI/UX.

• Analytics & science:

  Variance/standard costing, root-cause, forecasts (demand/RM prices), anomaly detection.

• Financial analytics:

  Standard costing, variance analysis, pricing/margin views, cash-flow trackers.

• Governance:

  Data quality checks, version control, documentation, role-based access, and SLAs.

• Tooling:

  Evaluate & deploy new tech (APIs, LLMs, RPA) where ROI is clear.

Key Areas

• Purchase
• Production
• Operations / Supply chain
• Sales
• Finance
• HR

Must-Haves

• Programmer:

  Strong Python + SQL; APIs/ETL; MS Office (Excel, Power Automate, Power Apps)

• Data-obsessed & analytical

  with solid statistics.

• Financial sense:

  Reads P&L/BS/Cash-flow; links ops metrics to margin/ROCE.

• Good design taste (UI/UX):

  You care about clarity and speed.

• Problem solver:

  Ships iteratively; simplifies messy factory data.

• Leverages new tools

  to avoid manual work and avoid hiring sprawl.
• Experience in Manufacturing Industry is a plus.