Open to opportunities

Himani Bansal

@himanibansal

Message

Assistant Manager turning SAP and data into automated Power BI dashboards and ERP improvements.

India

Message

What I'm looking for

I’m looking for a role where I can leverage SAP ERP, SQL, and Power BI to automate reporting and build reliable data pipelines—partnering cross-functionally to deliver measurable operational and financial impact.

I’m currently an Assistant Manager at JSW Steel Limited, analyzing financial and operational data from SAP ERP using SQL, Excel, and Power BI. I automate reports and dashboards, saving 15+ hours/week and improving data accuracy, while leading end-to-end ERP projects from requirement gathering to deployment.

Previously, as a Software Engineer Intern at GAIL (India) Limited, I built a GPT-based internal chatbot using Python (Transformers, OpenAI API), and completed data analysis with SQL, Pandas, Seaborn, and Scikit-learn to reach 95% accuracy. I enjoy partnering across Finance, HR, Production, Marketing, and Technical teams to turn raw inputs into dependable KPIs through ETL, data modeling, and interactive dashboards.

Experience

Work history, roles, and key accomplishments

Current

Assistant Manager

Current

JSW Steel Limited

Sep 2024 - Present (1 year 6 months)

Analyzed financial and operational data from SAP ERP using SQL, Excel, and Power BI to identify patterns, anomalies, and process inefficiencies. Built automated reports and dashboards that saved 15+ hours per week and led end-to-end ERP initiatives including bank reconciliation and audit/reporting automation.

SAP ERP SQL Excel Power BI Report Automation Dashboarding ERP Implementation Bank Reconciliation Audit Reporting

Software Engineer Intern

GAIL (India) Limited

Feb 2024 - Jul 2024 (5 months)

Developed a GPT-based internal chatbot in Python (Transformers, OpenAI API) to automate cross-department query resolution, reducing manual support. Built data analysis and reporting solutions using SQL, Pandas, Scikit-learn, and Plotly Dash, achieving 95% accuracy through iterative model tuning.