Shalini Donthireddy

Experience

• 

  Trigent Software Inc

  Sept 2019 - May 2020

  Data Analyst

  ● Analyzed 12 complex datasets from the Fraud Detection System over a year using Python and libraries like NumPy and Pandas, deriving actionable insights for organizational decision-making.● Crafted 20+ SQL queries in MySQL to retrieve, manipulate, and transform large datasets related to fraudulent activities, ensuring comprehensive analysis and reporting.● Formulated an SQL query to identify high-risk transactions by joining transaction logs with user account details and applying anomaly detection thresholds.● Designed 4 ETL pipelines using Azure Data Factory to integrate data into the organization’s data warehouse for seamless Fraud Detection System operations.● Facilitated advanced analytics and machine learning tasks on the Fraud Detection System using Azure Databricks, enhancing big data processing workflows to improve detection algorithms.● Created 5 Tableau dashboards to visualize key fraud detection metrics, enabling stakeholders to monitor fraudulent patterns and make data-driven decisions.● Developed 6 interactive dashboards and 10 detailed reports using MS Excel, presenting insights on fraudulent patterns to stakeholders and executive leadership. Show less

• 

  Capgemini

  Jun 2020 - Jul 2022

  ● Streamlined data pipelines using SQL, reducing manual data processing time by approximately 120 hours monthly, enhancing overall team productivity, and improving reporting accuracy.● Designed and built scalable data pipelines using Python and Azure Data Factory, automating data ingestion and processing from various sources into Azure Blob Storage and Synapse Analytics. ● Automated ETL workflows with SSIS, reducing data integration turnaround time by an average of 5 hours per dataset and ensuring seamless data transfer across systems.● Led the deployment of Azure Data Lake, improving data retrieval speeds by 10 minutes per query on average and supporting the storage of over 5 TB of structured and unstructured data.● Enhanced reporting and analytics by integrating Azure Synapse Analytics, reducing query processing time from an average of 15 minutes to under 5 minutes for large datasets.● Formulated interactive Tableau dashboards, delivering real-time insights that reduced manual reporting efforts by 10 hours per week and improved financial analysis timelines.● Established comprehensive Data Governance protocols for managing over 200 client datasets, ensuring compliance with regulatory standards and improving the consistency and reliability of reporting outputs.● Conducted in-depth Data Mining to identify actionable insights from large datasets, enabling strategic decision-making and uncovering hidden business opportunities.● Implemented Jenkins and Docker to automate CI/CD pipelines, reducing model deployment time from 8 hours to 2 hours and increasing the frequency of updates for production systems.● Executed data transformation workflows using Excel and integrated systems, improving operational efficiency effort. Show less ● Conceptualized SQL to write 15+ queries in PostgreSQL for data extraction and transformation, aiding project-specific analyses.● Processed and cleaned datasets containing approximately 5,000 rows, ensuring accurate inputs for analytics.● Designed 3 interactive dashboards in Tableau, providing stakeholders with actionable insights on business performance.● Automated 5 repetitive data workflows using KNIME, saving hours of manual processing time.● Executed analysis of historical data using SQL, identifying trends that supported departmental budgeting decisions.● Performed quality checks on datasets weekly to maintain integrity and resolve inconsistencies, improving report reliability. Show less

  • Data Analyst

    Oct 2020 - Jul 2022

  • Data Analyst Intern

    Jun 2020 - Sept 2020
• 

  Southern Illinois University, Carbondale

  Jan 2023 - May 2024

  Graduate Assistant

  ● Managed and processed sensor-generated streaming data with Azure IoT Hub, setting a 5-minute update interval to support timely decision-making and analysis.● Diagnosed and corrected data collection issues, implementing solutions that improved processing workflows and bolstered system reliability.● Conceptualized Azure Stream Analytics to handle and analyze 7+ GB of streaming data, enhancing the speed and accuracy of real-time sensor insights.● Linked Power BI to Azure Data Lake Storage to develop 5+ interactive dashboards and real-time reports, visualizing soil moisture and fertilizer metrics for the research team.● Optimized data processing methods to elevate overall system performance and efficiency, thereby refining data workflows. Show less

• 

  McKinsey & Company

  Jul 2024 - now

  Data Analyst

  ● Developed Python-based ETL pipelines to process and analyze operational datasets, improving data processing efficiency and reducing manual data handling time by 4 hours per week.● Maintained RESTful APIs to integrate data systems across departments, enabling smoother data transfer between two critical teams and enhancing daily workflows for five key users.● Built interactive dashboards using Power BI to provide actionable insights for managers, leading to more informed decision-making for three operational teams weekly.● Architected a robust cloud-based data infrastructure leveraging Azure Blob Storage and Synapse Analytics, enabling seamless storage and processing of extensive data at scale, which supported a considerable increase in concurrent user access without performance degradation. ● Conducted statistical analysis using Python libraries (NumPy, Pandas, Matplotlib) to examine operational performance patterns, contributing to real-time adjustments in resource allocation.● Created SQL queries to extract and transform operational data, reducing query runtime by 3 minutes per task and improving reporting efficiency.● Collaborated with cross-functional teams to redesign tracking systems for key processes, improving data accuracy for ongoing projects and enhancing overall workflow efficiency.● Applied data mining techniques to identify anomalies in resource management, saving an estimated 1 hour per week in manual checks and improving data consistency.● Automated reporting workflows using Django, ensuring the accurate and timely delivery of key operational metrics, reducing weekly report preparation time by 30 minutes. Show less