Data Analyst Business

Jishnu Minal Vakharia

*****, ********** **** **, *****, FL, USA - 33647

+1-469-***-**** **************@*****.*** Jishnu Vakharia SUMMARY

Business Data Analyst with 4 years of expertise in end-to-end analysis, from understanding business needs and gathering requirements to developing and implementing scalable solutions and delivering impactful insights across finance, risk, operations, and healthcare domains. Proficient in utilizing SQL, Python, and Power BI for data extraction, transformation, visualization, and analysis. Demonstrated ability to translate complex data into actionable strategies, optimize performance, and effectively communicate findings to drive strategic decision-making and business growth.

WORK EXPERIENCE

IRIS Software Client - CITI Bank Sep 2023 - Present Business Data Analyst Tampa, FL, USA

• Implemented customer flagging and processing architecture across multiple regions by transitioning from an account-based approach to a customer-centric methodology, aligning with global risk frameworks and regulatory standards, and reducing data discrepancies by 25%.

• Led reconciliation of 10M+ records across AML and KYC systems using advanced SQL queries and Python automation scripts to ensure cross-system data integrity.

• Built Jira dashboards to automate weekly executive reporting, reducing manual efforts by 40% and improving decision-making timelines.

• Streamlined the KYC application by refining operational workflows and data management practices, resulting in significant time savings for Operational Analysts.

• Integrated REST APIs between KYC and AML systems to automate risk assessment and transaction summaries, cutting processing time by 20%.

• Supported UAT and SIT by tracking, and resolving over 150+ defects to ensure production-readiness and quality.

• Conducted business requirement workshops with global stakeholders using Jira and Confluence to align project deliverables with compliance goals.

Accenture Feb 2021 - Dec 2021

Associate Consultant Bengaluru, KA, IND

• Created scalable ETL pipelines using AWS to ingest, transform, and load multi-terabyte datasets into cloud data warehouses, improving data flow and reducing query latency.

• Designed interactive Power BI dashboards visualizing KPIs such as turnaround time, SLA compliance, and error rates, enabling real-time decision-making for operations managers.

• Analysed revenue cycle and transaction data using complex SQL queries to identify delays and redundancies in claims processing and billing workflows, implementing optimization strategies that improved operational efficiency by 15%.

• Utilized Hadoop ecosystem tools including HDFS, MapReduce, Hive and Pig to process unstructured revenue data, uncovering patterns in claim denials and payment delays that informed process automation strategies and improved revenue recovery.

• Partnered with stakeholders and data architects to define data warehouse schemas and reporting layers using ERD models and SQL views, accelerating monthly reporting cycles by 30%. Minal Vakharia Corporation May 2020 - Jan 2021

Associate Product Manager Hyderabad, TS, IND

• Deployed predictive classification models using Naive Bayes and K-Nearest Neighbours (KNN) to assess loan uptake and repayment probability based on customer demographics and behavioural patterns. Performed full-cycle modelling that included feature engineering, cross-validation, and performance tuning to generate actionable insights.

• Insights derived from the models directly influenced product strategy, enhancing customer segmentation and boosting targeting precision across loan campaigns.

• Supported data-driven loan campaigns in collaboration with Bank of Baroda, contributing to over $1M in disbursed loans and a measurable increase in product adoption and customer engagement. Tejoma Technologies Jan 2020 - Apr 2020

Data Analyst Hyderabad, TS, IND

• Developed an automated tool to detect anomalies in bank statements by analysing transaction flows and customer activity, uncovering potential money laundering cases and strengthening financial compliance.

• Analysed over 1,000 datasets to identify unusual transaction behaviours across customer profiles, transaction channels, and historical trends, significantly improving fraud detection accuracy.

• Cleaned and transformed raw financial data to enhance model performance by removing outliers, imputing missing values, and eliminating redundant features, achieving a model accuracy of 92%.

• Conducted root cause analysis to uncover key behavioural patterns and transaction anomalies that indicated high-risk or fraudulent activity, enabling proactive risk mitigation. EDUCATION

The University of Texas at Dallas Jan 2022 - May 2023 Master of Science, Business Analytics

• GPA: 3.86/4

Dallas, TX, USA

Jawaharlal Nehru Technological University Aug 2016 - May 2020 Bachelor of Technology, Computer Science and Engineering

• GPA: 3.7/4

Hyderabad, TS, IND

TECHNICAL SKILLS

• Programming: SQL, Python, R

• Data Visualization: Power BI, Tableau, Excel

• Cloud Technologies: AWS, Azure Data Factory

• Analytics Techniques: Regression, Forecasting, Machine Learning, Anomaly Detection, ANOVA

• Other Tools: Jira, Confluence, Salesforce

Certifications

• International Institute of Business Analysis (IIBA) - ECBA

• AWS Cloud Practitioner

• Salesforce Certified Administrator

KEY PROJECTS

High Risk Customer Flagging

• Built a robust system architecture integrating KYC and AML platforms to flag, manage, and monitor high-risk customers in alignment with global risk frameworks and regulatory standards.

• Developed automated risk scoring models using customer transaction patterns and profiles to classify risk tiers, reducing manual reviews by 35% and improving response time.

• Partnered with compliance and legal teams to validate risk workflows and ensure full alignment with FATF, OFAC, and regional AML regulatory requirements, enhancing audit readiness. Portfolio Diversification

• Applied K-Means clustering to sector performance and volatility metrics within S&P 500 data to optimize portfolio composition, resulting in a 12% reduction in risk exposure.

• Automated extraction and preprocessing of financial data from live API feeds using Python scripts, enabling timely portfolio rebalancing and responsiveness to market shifts.

• Delivered actionable insights to stakeholders through Power BI dashboards, driving data-backed investment strategies. Loan Targeting Model

• Designed a predictive model using Python and SQL to analyse customer demographics and behavioural data, increasing loan targeting efficiency by 20%.

• Engineered key input features including credit utilization and repayment history patterns, significantly boosting model accuracy and segmentation precision.

• Performed A/B testing to validate model effectiveness, resulting in a 15% increase in loan approvals while maintaining stable risk exposure levels.

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