Data Analyst Integration

JAHNAVI BATTU

***********@*****.*** +1-773-***-****

PROFESSIONAL SUMMARY

Data Analyst with 4+ years of experience supporting data-driven decision making in technology and analytics-focused environments. Skilled in designing and optimizing SQL queries, stored procedures, and ETL pipelines using Oracle 10g and Exadata platforms. Adept at data integration, schema validation, and data lineage tracking to ensure accuracy and regulatory compliance, including experience with KYC platforms and wholesale credit product data. Proficient in Microsoft Excel and PowerPoint for building dashboards and presenting data insights to diverse audiences. Brings a detail-oriented approach to developing test scenarios, solution validation, and process improvements in Agile teams. Strong track record of managing multiple projects, guiding team efforts, and delivering high-quality solutions within fast-paced and evolving business contexts.

EDUCATION

Masters in Computer Science, Chicago, Illinois

DePaul University

TECHNICAL SKILLS

Databases: Oracle 10g, Oracle Exadata, PL/SQL, Stored Procedures

Agile & Testing Tools: Agile Scrum, Test Scenarios, Validation Scripts

Data Integration & ETL: ETL Pipelines, Python, Schema Validation, Data Lineage Tracking

Data Analysis & Query Tools: SQL Diagnostics, Complex Queries, Query Templates, Data Mapping

Client Onboarding & Compliance: KYC Platforms, Data Reconciliation, Wholesale Credit Products

Business Intelligence & Reporting: Microsoft Excel, Excel Dashboards, Microsoft PowerPoint, Data Visualizations

WORK EXPERIENCE

Abridge, Data Analyst Feb 2024 - Present

●Developed and maintained complex PL/SQL queries and stored procedures in Oracle 10g to support analytics on clinical conversation data, ensuring integrity and security of sensitive healthcare information.

●Built and optimized ETL pipelines using Oracle Exadata and Python to process large volumes of audio-transcript and EHR integration data for downstream analytics and reporting.

●Created comprehensive data models and documentation using Microsoft Office tools, making it easier for both technical and non-technical stakeholders to understand data flows and business rules.

●Improved data validation and quality control by implementing schema validation and lineage tracking within Oracle environments, minimizing data inconsistencies across evaluation workflows.

●Designed test scenarios for new data products and services, working closely with analysts and engineers to confirm solutions met business requirements before moving to production.

●Used strong analytical skills and attention to detail to diagnose and resolve data anomalies, utilizing monitoring tools and SQL diagnostics to maintain reliable data pipelines.

●Participated in Agile scrum ceremonies, helped prioritize user stories, and estimated effort for analytics and ML data integration tasks, supporting fast-paced development cycles.

●Developed and maintained real-time data ingestion systems, ensuring timely surface of unstructured clinical data for machine learning evaluation and production scoring.

●Contributed to requirement refinement discussions by translating technical details into clear business language, supporting communication between engineering teams and business stakeholders.

●Supported advanced analytics initiatives by preparing and delivering presentations using Microsoft PowerPoint and Excel, highlighting trends and actionable insights to product managers and leadership.

Gradient AI, Data Engineer Jun 2021 - Aug 2023

●Developed and optimized advanced PL/SQL queries and stored procedures within Oracle 10g and Exadata environments to support risk analytics and regulatory reporting for wholesale credit products.

●Built automated Microsoft Excel dashboards and data visualizations for tracking onboarding and KYC progress, enabling business users to quickly identify compliance gaps across multiple client portfolios.

●Created detailed test scenarios and validation scripts to ensure robust data integration between client onboarding platforms and legacy core banking systems, minimizing interface defects and reconciliation issues.

●Designed data mapping solutions connecting wholesale credit data from multiple applications, supporting seamless end-to-end business process reviews and root cause analysis of transaction delays.

●Delivered technical and business presentations to executive leadership and IT teams, clarifying project status and summarizing analysis results using PowerPoint and detailed Excel models.

●Participated in Agile sprint planning and story refinement sessions, contributing to workload estimation and prioritization of deliverables for data migration and onboarding initiatives.

●Implemented innovative data reconciliation methods to detect and resolve discrepancies in KYC records, improving overall data integrity for compliance and audit readiness.

●Improved team productivity by building query templates for ad hoc analysis of large financial datasets, supporting quick turnaround for urgent risk and compliance requests.

●Supported financial effort estimation by analyzing historical project data, helping the team accurately allocate resources across simultaneous onboarding and KYC projects.

●Worked collaboratively with cross-functional teams to troubleshoot complex data integration issues, frequently reaching out to subject matter experts when necessary to accelerate issue resolution.

PROJECTS

File Retrieval Engine

Developed a C++ multithreaded client-server engine with ZeroMQ and the Dispatcher Design Pattern.

Implemented thread-safe procedures into scalable document indexing and search.

created a file retrieval CLI and tested it using CMake and GDB on Linux and Windows.

Portfolio Craft

Built a full-stack web app using React (frontend), Spring Boot (backend), and MySQL.

Integrated Sapling SDK and APIs; improved response time by 25% and achieved 99.9% AWS uptime.

Used Postman for testing, GitHub for version control, and deployed on AWS.

Fast detection of multiple objects in traffic scenes using a common detection framework

This project aims to swiftly detect multiple objects in traffic scenes using a unified framework, facilitating enhanced safety and efficiency in traffic management.

Developed an OpenCV-based real-time object detection system that can process massive traffic datasets quickly and accurately.

increased precision in identifying cars, pedestrians, and safety signage.

Created a powerful visual module for quick processing and judgment.

Prediction Probability of getting Admission into a University using Machine learning

Built a prediction model in Python using scikit-learn, NumPy, and Pandas.

Focused on preprocessing, model validation, and interface design for usability.

Delivered accurate admission predictions with a clean user-friendly UI.

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