Looks like you have JavaScript disabled. For the full Twine experience, you will need to re-enable it.

Hi, I'm Ankita Shigwan, a data analyst specializing in FinTech with 5 years of experience leveraging Python, SQL, and advanced analytics to improve product performance and financial decision systems. I design financial models and forecasting to support strategic decisions and optimized portfolio performance. I'm proficient in SQL, Excel, Power BI, and Tableau for reporting, trend analysis, and data visualization. I excel at translating complex financial datasets into clear, business-critical insights for stakeholders and collaborating across teams to improve process efficiency, risk management, and revenue growth.…Hi, I'm Ankita Shigwan, a data analyst specializing in FinTech with 5 years of experience leveraging Python, SQL, and advanced analytics to improve product performance and financial decision systems. I design financial models and forecasting to support strategic decisions and optimized portfolio performance. I'm proficient in SQL, Excel, Power BI, and Tableau for reporting, trend analysis, and data visualization. I excel at translating complex financial datasets into clear, business-critical insights for stakeholders and collaborating across teams to improve process efficiency, risk management, and revenue growth.

Ankita Shigwan

Data Scientist, Data Analyst, Programmer, +2





Hi, I'm Ankita Shigwan, a data analyst specializing in FinTech with 5 years of experience leveraging Python, SQL, and advanced analytics to improve product performance and financial decision systems. I design financial models and forecasting to support strategic decisions and optimized portfolio performance. I'm proficient in SQL, Excel, Power BI, and Tableau for reporting, trend analysis, and data visualization. I excel at translating complex financial datasets into clear, business-critical insights for stakeholders and collaborating across teams to improve process efficiency, risk management, and revenue growth.…Hi, I'm Ankita Shigwan, a data analyst specializing in FinTech with 5 years of experience leveraging Python, SQL, and advanced analytics to improve product performance and financial decision systems. I design financial models and forecasting to support strategic decisions and optimized portfolio performance. I'm proficient in SQL, Excel, Power BI, and Tableau for reporting, trend analysis, and data visualization. I excel at translating complex financial datasets into clear, business-critical insights for stakeholders and collaborating across teams to improve process efficiency, risk management, and revenue growth.

Available to hire

Hi, I’m Ankita Shigwan, a data analyst specializing in FinTech with 5 years of experience leveraging Python, SQL, and advanced analytics to improve product performance and financial decision systems. I design financial models and forecasting to support strategic decisions and optimized portfolio performance.

I’m proficient in SQL, Excel, Power BI, and Tableau for reporting, trend analysis, and data visualization. I excel at translating complex financial datasets into clear, business-critical insights for stakeholders and collaborating across teams to improve process efficiency, risk management, and revenue growth.

Skills

Experience Level

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Expert

Language

English

Fluent

Work Experience

Financial Data Analyst at Fidelity Investments

May 1, 2015 - Present

Engineered predictive portfolio models using Python and SQL, integrating anomaly detection and credit risk forecasting to strengthen investment decision-making for $500M institutional portfolios; reduced high-risk exposure by 12%. Spearheaded Power BI dashboards visualizing KPI metrics, portfolio optimization, and asset allocation, informing executives on 20+ investment sectors and improving resource allocation by 22%. Automated reporting pipelines via Airflow, leveraging AWS S3 and Redshift to storage data and analytics, reducing weekly reporting effort by 120 hours while maintaining GAAP and SOX compliance. Analyzed portfolio P&L, stress testing, and scenario studies, highlighting potential losses up to $5M. Designed cloud-based forecasting on AWS (Athena) and QuickSight to improve liquidity forecasting for $200M cash flows.

Data Analyst at Deloitte

January 1, 2022 - February 1, 2023

Led end-to-end development of scalable financial analytics pipelines using Python, SQL, PySpark, and Databricks, automating reconciliation, settlement validation, and fraud monitoring workflows reducing manual effort by 35-40%. Designed advanced ETL frameworks to ingest high-volume transaction, ledger, risk, and customer behavioral data, enabling faster fraud checks, dispute resolution, and regulatory reporting (KYC/AML/PCI). Owned data validation frameworks with automated profiling, anomaly detection, and auditing logic to ensure regulatory-grade accuracy for payments and digital banking clients. Built high-impact Tableau/Power BI dashboards tracking fraud alerts, credit risk KPIs, chargeback trends, liquidity metrics, revenue leakage, and operational SLAs. Mentored junior analysts, reviewed code/queries, and introduced best practices for CI/CD, documentation, and reusable analytics modules.

Associate Data Analyst at Deloitte

January 1, 2019 - December 1, 2021

Supported the development of automated workflows for payments processing, reconciliation, and transaction monitoring using Python and SQL, reducing manual effort by 20% and improving reporting accuracy across operational teams. Built ETL pipelines in Databricks (PySpark, SQL) to transform large transaction datasets into analytics-ready tables, ensuring KYC/AML-aligned data quality and validation. Utilized AWS (S3, Lambda, EC2) to manage and optimize financial data storage and reporting pipelines, and developed interactive Tableau/Power BI dashboards to monitor payment volumes, exception trends, and operational performance. Collaborated with product owners and QA teams in Agile sprints to gather requirements, perform UAT, and document process updates, delivering clear insights on anomalies, bottlenecks, and emerging trends to leadership.