Data Analysis Machine Learning Storytelling & Dashboarding Financial Modeling
Learn more I work on breaking complicated business problems into
simple components and apply advanced analytics to generate actionable insights.
A graduate of the MS in Financial Technology & Analytics program
from University of Texas - Dallas.
I have undertaken projects in Dashboarding, Causal Analytics, Machine Learning,
Root Cause Analysis, Statistical Analysis, Credit Risk Analytics, Data Validation and Database Management.
I optimize processes using data!
Experienced in analyzing large sets of data to design and develop data systems
and reporting tools to ensure that the business and clients
team members have the product, support, and operations data
needed to make crucial business decisions. I have also had the
opportunity to create coplex financial models to generate portfolio recommendations for clients to invest in the Equities and Derivatives Market.
Proficient with Python, SQL, Tableau, Pandas, NumPY, Matplotlib, Seaborn, Scikit-Learn, and more, I can help simplify data and identify bottlenecks and analyse the scope of using advanced analytics on the problem.
Along with being a vivid believer in using data to tell a story I also hold expertise in breaking complicated problems into simple components to identify all the moving parts of the process. As a Financial Analyst at ATM Capital, I have first hand experience in creating KPI's and automating dashboards for customer centric process and also for tracking the data quality.
I have had the opportunity to work on analyzing the effectiveness of marketing campaigns for Sonal Gems enabling them to make smarter marketing decisions and effectively operate their strategies and insights. Using a range of formats and marketing channels, I can develop campaign-level concepts, test for their effectiveness, and recognize actions that increase conversions and customer engagement.
Well acquainted with machine learning, deep learning, natural language processing. Have undertaken projects in building models for predicting the default rate on loans and determine the credit worthiness of a customer. I can work of developing and improving the existing models in your company.
Look here for a collection of my latests projects, articles, and more.
June 2024 - August 2024
• Developed automated SEC filing parser using python to scrape and parse 10-K filings and metadata of over 5000 firms to create a database for FY2023
• Analyzed participation of firms in reverse factoring and details of their disclosed obligations under ASU 2022-04 using Natural Language Processing
• Created a SQL Database of over 5000 firms and identified 67 firms that disclosed their reverse factoring obligations as per ASU 2022-04
January 2021 - August 2022
• Conducted comprehensive analysis of stock market data using Excel, Python, and SQL, resulting in optimized data pipelines and actionable insights for portfolio management
• Implemented data cleansing, transformation, and aggregation processes, improving data quality and enabling more accurate financial modeling
• Collaborated closely with investment teams to understand data requirements and develop scalable solutions for portfolio analysis and risk management
• Designed algorithms and automated processes to analyze market trends and forecast investment opportunities, contributing to enhanced portfolio performance and risk mitigation
• Developed and implemented financial models using Python and SQL to provide strategic investment recommendations, leading to over $1M in annual brokerage revenue
• Created and maintained interactive dashboards using Tableau and Power BI, enabling stakeholders to visualize and interpret complex financial data effectively
April 2015 - June 2018
• Implemented a centralized vendor information system, enhancing data accuracy and retrieval efficiency by 15% through effective data integration strategies and automation using SQL and ETL tools
• Developed automated invoicing processes using Excel and SQL, reducing errors by 20% and speeding up processing time by 30%, ensuring seamless data flow and integrity
• Captured, validated, and processed data for monthly financial reports (P&L statements, balance sheets, cash flow statements) using advanced Excel and SQL, leading to a 10% increase in financial reporting efficiency.
• Assisted with analysis, design, and testing of report enhancements, contributing to a 15% increase in forecast accuracy
• Conducted trend analysis and presented findings through dashboards, aiding strategic decision-making, resulting in a 12% improvement in cost management and a 10% increase in market share.
• Analyzed customer purchasing behavior with Python & SQL, provided insights for marketing campaigns & increased customer retention by 8%
• Designed interactive dashboards in Tableau and Power BI to track KPIs, sales performance, and inventory levels, improving inventory turnover by 25% and providing actionable insights for operational efficiency.
• Created ad-hoc reports and visualizations for management, facilitating quick decision-making and resulting in a 15% increase in operational efficiency.
August 2022 - August 2024
UTD's Master of Science in Financial Technology & Analytics (MS Ftech) teaches students how to extract insights with creative data analysis, and then apply the results in real business settings. Students graduate with a unique combination of data science skills and business acumen to lead in an increasingly data-driven world.
Data Science & Analytics Courses:August 2018 - May 2021
The course is specifically designed to develop the logical and technical skills of students interested in computer science or industrial computing.
The course helps in developing professional competence in software designing and its implementation.
The institution values the importance of substantial infrastructure requirements and qualified faculties to run this highly professional course.
Seattle, WA
98121 USA
Phone: (564) 202 - 3121