Krishnaveni Sanikommu
@krishnavenisanikommu
I build real-time fraud detection, risk scoring, and transaction monitoring systems for FinTech payments.
United StatesWhat I'm looking for
I've built fraud detection and risk decisioning workflows at Credit Karma (Intuit) to monitor 100K+ transactions per day, automate transaction monitoring, and reduce manual review effort by 20%.
Across Stack Payments, Dwolla, and Bank of the West, I've developed chargeback prediction, merchant risk, anomaly detection, and transaction forecasting solutions. I use Python, SQL, Kafka, PySpark, Airflow, AWS, and machine learning to move from data ingestion and feature engineering through deployment and business reporting.
At Stack Payments, I led chargeback prediction and risk-tier classification work for payment data, supported by real-time Kafka and PySpark pipelines. At Dwolla, I built time-series forecasting and anomaly detection workflows and delivered Tableau and QuickSight dashboards for finance, sales, and compliance teams.
I've also applied NLP and customer analytics at StubHub, including a chatbot with 92% accuracy, sentiment analysis, and predictive sales models. I focus on practical, KPI-driven systems that help fraud, risk, operations, and compliance teams investigate faster and make better decisions.
Experience
Work history, roles, and key accomplishments
Built and deployed real-time fraud detection and risk decisioning workflows, supporting monitoring of 100K+ transactions/day. Developed and optimized fraud rules and risk scoring logic, improving fraud signal detection and reducing manual review effort by 20%.
Data Analyst / Fraud Analyst
Bank of the West
Feb 2025 - Jun 2025 (4 months)
Built interactive Tableau dashboards and reporting systems to monitor suspicious transactions and fraud patterns across banking operations. Developed daily, weekly, and monthly fraud reports covering key metrics such as flagged transactions and unauthorized transaction volumes by channel.
Data Scientist – Fraud & Risk Intelligence
Stack Payments
May 2023 - Jul 2024 (1 year 2 months)
Led a chargeback prediction project to reduce financial losses and enhance fraud detection using AWS Redshift, Kafka, Pyspark, and Prophet for real-time data processing and forecasting. Developed and deployed machine learning models in Python, implemented CI/CD pipelines with GitHub Actions, and created interactive Dash visualizations.
Predicted daily and weekly client transactions using Time Series models (FB Prophet) and Pyspark for large-scale forecasting. Implemented anomaly detection systems to identify irregular transaction patterns and potential fraud risks.
Developed an AI-powered chatbot using NLP, NLTK, and TF-IDF with 92% accuracy, reducing manual responses and increasing customer engagement. Conducted sentiment analysis on customer reviews using XGBoost to inform product and marketing strategies.
Associate Data Scientist
SynergisticIT
Nov 2019 - Dec 2020 (1 year 1 month)
Built a car price prediction model using Linear Regression in Python; evaluated performance with R2 and Adjusted R2 metrics. Collaborated with data engineers to integrate databases and streamline data flow using Python.
Education
Degrees, certifications, and relevant coursework
Osmania University
Master of Business Administration, Human Resources
Pursued a Master of Business Administration with a focus on Human Resources.
Kakatiya University
Bachelor of Science, Mathematics, Statistics, and Computer Applications
Earned a Bachelor of Science with a triple major in Mathematics, Statistics, and Computer Applications.
Availability
Location
United StatesAuthorized to work in
Social media
Job categories
Skills
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