Lavanya Pittla

• Spearheaded the development and deployment of predictive models using Python (Pandas), enhancing customer churn prediction accuracy by 15%, which contributed to a 10% increase in customer retention.
• Optimized operational processes by automating manual tasks with Power Automate and Python scripting, resulting in a 20% reduction in processing time and a 15% improvement in efficiency across the Healthcare, FMCG, and Finance sectors.
• Created dynamic dashboards in Power BI and DAX to effectively track key performance indicators (KPIs), empowering data-driven decision-making and boosting operational efficiency.
• Performed detailed exploratory data analysis (EDA) using Python libraries to uncover hidden patterns and trends, which led to the identification of new market opportunities.
• Ensured high data integrity and accuracy through thorough validation using MySQL, Python, and Excel.
• Developed and implemented ETL processes using Power Query and Python (Pandas, NumPy) to streamline data extraction, transformation, and loading from diverse sources.
• Worked closely with cross-functional teams to ensure the successful delivery of complex projects within established timelines.

Project: Google-GDO-HD Mapping

• Reviewed & Processed RFL (Request for Labeling) and RFQ (Request for QC) data to determine lane and attribute requirements for regions including Canada, Belgium, and Denmark using ArcGIS and GeoPandas
• Created and digitized lanes and attributes per RFL guidelines, ensuring accurate data representation in mapping systems
• Utilized GIS tools like QGIS and ArcGIS to efficiently process and analyze geo-spatial data in alignment with company protocols
• Ensured data accuracy by cross-verifying with satellite imagery, road signs, and local regulations via ArcGIS & GeoPandas tools
• Worked with Quality Analysts, Data Managers, and Pod Leads to resolve data discrepancies and deliver reliable outputs.

· Leveraged advanced Excel skills to source candidates through job boards and social media, resulting in a 10% increase in candidate pool size.

· Streamlined recruitment processes by automating databases and generating insightful MIS reports using Pivot Tables, VLOOKUP, HLOOKUP, INDEX-MATCH, and Excel Macros, leading to a 15% reduction in recruitment time.

· Developed and implemented Excel-based evaluation sheets to accurately assess candidate fit, improving hiring quality by 8%.

Collaborated with stakeholders to refine data analysis processes and produce comprehensive MIS reports that provided valuable insights into recruitment trends, enhancing operational transparency.