Product and Data Focused Technologist

Building systems that connect, optimize & scale

Over 5 years in ERP integrations, system optimization, and cross-functional delivery. Led high-impact projects for LinkedIn — defining product requirements, improving customer experiences, and aligning technical execution with business strategy. Completed MSIS at UW, expanding into product management, cloud technologies, and data-driven decision making.

View My Work ↓ Get in Touch

About

MSIS @ University of Washington

Seattle, WA

Open to product management, and data engineering opportunities

Years Experience

2025

MSIS @ UW

Enterprise Projects

What I Do

Skills & Expertise

From enterprise systems to machine learning pipelines, I bring a blend of product thinking and technical execution.

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Product Management

End-to-end feature lifecycle ownership · Product roadmap development · Prioritization · User story creation · PRD writing · Requirements gathering · Scope management · Launch planning · Iteration

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Methodologies & Frameworks

Agile/Scrum · Waterfall · SDLC · CI/CD Concepts · Requirements Analysis · Sprint Planning · Retrospectives · Backlog Grooming

❮/❯

Technical Proficiency

Python · SQL · PL/SQL · ETL Pipeline Design · Data Integration · Cloud Platforms (Azure, Snowflake) · Data Quality Assurance · Oracle EBS

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Tools & Platforms

Jira · ServiceNow · Confluence · SharePoint · Microsoft Project · Microsoft Suite · Tableau · Figma · Git · Docker (basics)

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Soft Skills

Cross-functional Collaboration · Executive Communication · Conflict Resolution · Team Mentoring · Process Improvement · Change Management

Portfolio

Projects & Case Studies

Highlights from enterprise work and academic research.

AI & Product Innovation

ML / Anomaly Detection · Apr 2026 – Jun 2026

Real-Time Anomaly Detection for Freight Logistics

Designed and deployed an ML system for Radiant Delivers (international freight forwarder) that flags data-entry errors in freight shipments before they cause downstream cost, running across 1.4M+ SAP Transportation Management documents. Owned the feature engineering and data modeling that fed the detection models, and built the real-time ingestion-to-inference pipeline end to end.

Isolation Forest Gaussian Mixture Model GCP / Vertex AI Pub/Sub & Cloud Run ClickHouse Streamlit

View Details →

AI / Multi-Agent System · Mar 2026

CRAPES — Chatbot Readiness & Performance Evaluation System

Led a team to design and deliver an automated chatbot evaluation platform, coordinating workstreams across frontend, backend, and AI model integration. Dual-LLM architecture eliminates self-evaluation bias and ensures objective security assessments aligned with OWASP LLM Top 10.

React Vercel Serverless Claude Gemini OWASP LLM Top 10

Defined scope, milestones, and acceptance criteria across iterative sprint cycles
Built prompt refinement engine and pre-assessment questionnaire for continuous quality improvement
Awarded Best Demo for innovation in LLM evaluation and practical applicability

View Case Study → GitHub

AI Pipeline · Jan 2026

Data Quality Pipeline with Claude Skills

Scoped and delivered a three-phase AI pipeline (Inspect, Clean, Report) automating data quality assurance for ERP/CRM-style datasets, reducing manual QA effort significantly.

Claude Prompt Engineering Data Quality HTML Reporting

Iterated through 3 prompt versions, tracking performance across 4 datasets
Achieved 100% detection accuracy on data quality issues with zero false positives
Produced professional HTML reports with executive summaries and remediation recommendations

GitHub

Data Analytics

Data Science · Dec 2025

Netflix Customer Churn Analysis

Built predictive models to identify high-risk Netflix subscribers using 5,000 records and 14 variables from Kaggle. Compared Logistic Regression and Random Forest models, performed K-Means clustering for customer segmentation, and delivered actionable retention strategies.

Python Logistic Regression Random Forest K-Means Clustering Google Colab

Random Forest achieved 94.32% accuracy (vs. 89.12% Logistic Regression)
Basic tier had highest churn at 61.83%; Premium lowest at 43.71%
K-Means identified 3 segments: inactive (90% churn), casual (42%), engaged (9%)
Recommended targeted retention offers for Basic-tier and low-engagement users

View Case Study → Slides

Academic Project

Seattle Crime Analysis

End-to-end data analysis on Seattle PD's 2024 crime dataset (81,771 reports) to uncover top offense types, hotspot neighborhoods, and time-based patterns. Built forecasting models to predict daily incident trends.

Python R Linear Regression Data Viz

Identified Larceny/Theft as the most common crime type
Hotspots: Capitol Hill, Downtown, Queen Anne, Northgate
Linear Regression (MAE 19.1) outperformed Random Forest (MAE 25.3)
Recommendations: targeted patrols, improved parking security

View Case Study → Report (PDF) Slides

Enterprise Systems

Enterprise Project

Global ERP Procurement Integration

Planned, designed, and implemented API-based data flows for Supplier, Requisition, PO, Invoice, and Payment modules between Oracle E-Business Suite and Coupa for a Fortune 500 client.

Oracle R12 PL/SQL Python REST APIs Middleware

Procurement efficiency improved by ~30%
Month-end reconciliation effort reduced by ~50%
Data accuracy across supplier/PO/invoice up ~35%
16-month, 2-phase rollout with zero Sev-1 incidents

View Project Details →

Enterprise Project

Automated Reconciliation Reporting

Partnered with finance stakeholders to deliver automated reporting for a Fortune 500 client, accelerating accounting processes by 50%.

PL/SQL Oracle Finance

Automated manual reporting workflows end-to-end
Accounting process acceleration of 50%
Reduced manual errors in financial reconciliation

Enterprise Project

SQL Query Optimization

Improved product performance by optimizing 6 critical queries for a Fortune 500 client, reducing financial reporting time by 25%.

SQL Performance Tuning Oracle

Optimized 6 critical database queries
Financial reporting time reduced by 25%
Improved overall product responsiveness

My Approach

How I Work

A structured, iterative process that balances business needs with technical feasibility.

Discover

Stakeholder interviews, workflow mapping, and problem definition

Design

Data mapping, API contracts, requirements, and architecture

Build

Iterative development, code reviews, and cross-team coordination

Verify

End-to-end testing, data validation, and UAT

Launch & Iterate

Go-live support, monitoring dashboards, and continuous improvement

My Journey

Career Timeline

Key milestones that shaped my path from enterprise IT to product-focused technologist.

Apr 2026 — Present

AI ML Intern

Radiant Logistics Inc., United States (Hybrid). Analysed SAP Transportation Management shipment data across Air, Sea, and Road freight modes covering 50+ attributes including weight, charges, tracking, and routing signals. Developed an automated anomaly detection pipeline using Isolation Forest models with SHAP explainability to flag and explain suspicious shipments, deployed on GCP Vertex AI. Built a data pipeline to load anomaly results into PostgreSQL and developed a real-time dashboard for operations teams to monitor shipment data quality across all freight modes.

Jan 2026 — Mar 2026

Teaching Assistant — TECHIN 535 Fundamentals of Technology Strategy

University of Washington, Seattle, WA. Supporting course delivery by grading assignments, tracking participation, and mentoring students in applying technology strategy frameworks to real-world business and product cases.

Dec 2023 — May 2025

Senior Software Engineer — Technical Project Lead

Accenture Solutions, Pune, India. Led cross-functional delivery of scalable data integration pipelines between Coupa and Oracle ERP, improving operational efficiency by 30%. Managed automated reconciliation reporting, accelerating accounting close by 50%. Translated 3 BRDs into functional and technical design specs.

Dec 2021 — Dec 2023

Application Development Analyst — Project Coordinator

Accenture Solutions, Pune, India. Coordinated optimization of 6 critical SQL reporting workflows, reducing execution time by 25%. Planned and executed automation initiatives using Python and Shell scripting, building scalable ETL solutions.

Sep 2019 — Dec 2021

Application Development Associate

Accenture Solutions, Pune, India. Managed delivery of 15 feature enhancements to Oracle E-Business Suite. Delivered production support with an average SLA of 2 days. Created technical documentation and conducted knowledge-transfer sessions.

Dec 2017 — Jan 2018

Website & App Development Intern

EventBeep, Pune, India. Collaborated with cross-functional design and development teams to implement responsive UI components and improve user accessibility across web and mobile platforms.

Nov 2016 — May 2017

Teaching Assistant — DBMS, Data Analytics & Statistics

Savitribai Phule Pune University, Pune, India. Conducted lectures, tutorials, and lab sessions for undergraduate students. Designed assessments ensuring academic rigor in database management and analytics.

Get In Touch

Let's Connect

Whether you'd like to collaborate, discuss opportunities, or just say hi — I'd love to hear from you.

shraddha.mahangare@gmail.com

linkedin.com/in/shraddha-mahangare

GitHub

github.com/smahanga

Resume

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