DEEPTHI DESHARAJU

• I was involved in the Financial Consumer Complaints Data Analysis project, where I utilized SQL, Power BI, Snowflake, ETL, and Python to automate data processes, create advanced visualizations, and optimize performance for insightful analysis and reporting.
• Developed multiple Tableau dashboards for various financial consumer complaint categories, providing insightful visualizations and data analysis to aid decision-making.
• Automated the extraction, transformation, and loading (ETL) process of financial consumer complaints data from multiple sources into Snowflake, using SQL and Python scripts to ensure data consistency and reliability.
• Utilized Snowflake's scalable data warehousing capabilities to store large volumes of consumer complaints data, enabling quick and efficient data retrieval for analysis and reporting.
• Designed and implemented data extraction and transformation processes using SQL and Python, improving data quality and performance. Applied custom transformations to handle missing values and anomalies.
• Optimized SQL queries and data models to improve performance, significantly reducing the data processing time and enhancing the efficiency of the ETL pipeline and visualizations.

Technology Stack: Snowflake, Oracle DB,ETL, Python (Scikit-Learn/NumPy/Pandas/Matplotlib),Tableau,Excel

• Developed multiple Dashboards and Reports for various business units, including Legal Attachments and Debit Card Fraud Security.
• Automated In-Complete Applications for Credit Card and Consumer Lending loans and scheduled reports for daily email distribution.
• Utilized Python for data cleaning, handling missing values, and performing anomaly detection, improving data quality and reliability for analysis by 25%.
• Applied hypothesis testing and statistical inference to identify significant trends and patterns in debit card fraud data.
• Developed Scatter Plots and Area Maps in Tableau to visually represent states with the highest and lowest debit card fraud incidences.
• Created SQL extract files to improve performance and reduce data load times.
• Used Tableau Desktop for blending databases and creating interactive views and dashboards.
• Updated and enhanced various Tableau reports, including reducing the number of rows brought back for a workbook from 142 million to 14 million, vastly improving performance.
• Revamped stale Tableau workbooks by creating dynamic functionality with parameters and actions, and visually enhancing design and user-friendliness.
• Converted multiple Tableau workbooks to SQL stored procedures, allowing the business to import tested and validated data without writing their own code.
• Designed and developed the Philips Product Sales Dashboard using complex tabular reports, bar charts, and bubble charts to provide better visualization.
• This helped in tracking business days involved in completing tasks associated with launching new Philips products as part of the national sales program.
• Developed various visualizations, including Gantt charts, waterfall charts, and geospatial visualizations for sales analysis purposes.
• These visualizations assisted the business in tracking critical paths involved in obtaining market approvals before the launch of a new Philips product.
• Developed custom SQL queries and data blends as per requirement.
• Involved in troubleshooting and performance tuning of reports and resolving issues within Tableau Server and reports.
• Included in weekly meetings, reviews, and user group meetings while also actively engaging with stakeholders and business groups through ongoing communication.
• Worked with Business Analysts to streamline data issues, which involved unit testing of all worksheets.
• Implemented the Philips High Sales Analysis Dashboard to monitor top-selling products, leading to data-driven decisions for enhancing product distribution and inventory management.
• Experimented with predictive models, including regression analysis, to forecast sales trends and improve business decision-making.

Technology Stack: Oracle DB, Python (Scikit-Learn/NumPy/Pandas/Matplotlib), Machine Learning (Logistic Regression/Support Vector Machine/Gradient Boosting/Random Forest/Linear Regression), Tableau, Hypothesis Testing, A/B Testing, Statistical Inference,Git,Docker.

• Led client engagement for the PRICE Dashboard project, ensuring alignment with client goals and project specifications
• Crafted and implemented user-friendly Tableau solutions, simplifying complex data into accessible visual formats
• Demonstrated innovation in the design of diverse charts and dynamic elements to enhance data visualization
• Orchestrated multiple Tableau Data Visualization projects, maintaining high standards of quality and timeliness
• Boosted data accuracy by 30% through the implementation of advanced SQL queries, enhancing the reliability of insights
• Resolved complex data analysis challenges, leveraging analytical skills to improve the decision-making process
• Enhanced business decision-making by providing clear, actionable insights derived from detailed data analysis.

Technology Stack: Sql Server, My SQL, Python, Tableau, ,Git, Docker.

• Played a dual role as Developer and Backup Project Lead for the Mint Wave-2 project at Tata Consultancy Services, enhancing the MPS system for CNA Investments to support Non MaxiMIS CUSIPs alongside MaxiMIS.
• Actively involved in gathering requirements from onsite coordinators and effectively managing an offshore team to ensure successful project deliveries.
• Contributed to design and implementation discussions, and responsible for creating and managing human tasks within business processes.
• Provided comprehensive production and testing support, including testing, debugging, defect fixing, and performance tuning of SQL, PL/SQL, and Shell Script code bases.
• Assisted team members with technical and business support and conducted essential training sessions to align the team with project requirements.

Technology Stack: Oracle DB, Unix,shell scripting,Control-M,PL/SQL.