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Hello, my name is

Shilpa Kumari

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Explore My

Experience

Engineer - Marelli (India) Private Limited

Feb 2024 - Jul 2024 | Bengaluru, India

  • Developed robust Android HMI modules (Radio, Phone, Device Manager) using Java and Android SDK, increasing user engagement by 60% for Stellantis.
  • Integrated AIDL and Jar APIs with middleware services to enhance system interoperability and modularity.
  • Optimized MVVM architecture and Observer patterns, resulting in a 70% improvement in application performance.
  • Collaborated with cross-functional teams including System Requirements and Validation to deliver high-quality code under strict Agile deadlines for critical client demos.

Java Kotlin AIDL API Integration MVVM architecture Observer Pattern

Junior Software Engineer - PeopleTech Enterprises Pvt. Ltd.

Nov 2021 - Jan 2024 | Hyderabad, India

  • Enhanced Android Automotive HMI for General Motors brands leveraging AOSP and Settings modules.
  • Executed full SDLC tasks including UI/UX design, integration, and defect resolution for scalable features.
  • Implemented secure fragment-based architectures adhering to Android Automotive security standards.
  • Maintained a 95% on-time delivery rate while authoring Espresso UI test cases to ensure regression stability across multiple screen densities.

Android Automotive HMI AOSP Java Kotlin Android SDK XML UI Gradle ADB
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Explore My

Skills

Technical Skills

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Java

Experienced

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Python

Experienced

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SQL

Experienced

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Android Developer

Experienced

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Data Analysis & Visualization

EDA

Feature Engineering

Power BI

Tools & Platforms

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Database

PostgreSQL

MongoDB

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Cloud & DevOps

AWS

Azure

Git

Jenkins

JIRA

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Orchestration

Dagster

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Development & IDEs

Jupyter Notebook

Visual Studio

Android Studio

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Know About My

Education

MSc in Data Analytics – National College of Ireland

Sep 2024 - Sep 2025 | Dublin, Ireland

  • Modules – Statistics, Data Governance, DAP, Business Intelligence, Machine Learning, Deep Learning, Generative AI
  • Research Proposal – Hybrid Federated Learning Aggregation Methods for Non-IID Time Series Energy Demand Forecasting Using Gated Recurrent Unit (GRU) Neural Networks.

B.E. in Electronics & Communication Engineering – Sagar Institute of Research & Technology

Sep 2016 - Sep 2020 | Bhopal, India

  • Modules – C & C++ Programming, Object-Oriented Programming using Java, Software Engineering Principles, Network Security, Wireless Communications, VLSI Design, Microprocessors & Microcontrollers, Digital Signal Processing.

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Browse My Recent

Projects

Seattle Crime Data Analysis Pipeline using Dagster

  • Built an automated pipeline to collect and process over 1M Seattle crime records into clean, analysis-ready data.
  • Used geospatial analysis to uncover neighborhood-level crime patterns across Seattle.
  • Created an interactive dashboard using Streamlit with maps and charts to explore and communicate insights.

Multi-Model Temporal Analysis of Soccer Matches

  • Developed and evaluated 4 sequence models (Transformer, CALF, etc.) for a 17-class event spotting task in soccer videos.
  • Utilised ResNet-152 for feature extraction, optimised training across 30 epochs, achieving stable and consistent model learning.
  • Implemented flexible training and evaluation pipelines, dockerising experiments for fair benchmarking and CALF model achieving top accuracy.

Distributed Crime Data Analytics Pipeline with Apache Spark

  • Designed and implemented a scalable Apache Spark ETL pipeline to ingest and process 5M+ Chicago crime records from a public API into AWS.
  • Performed Spark-based data transformations, and schema validation, loading curated data into PostgreSQL.
  • Delivered insights through a Streamlit analytics dashboard.

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Get In Touch

Contact Me

shilpasingh.aur@gmail.com

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LinkedIn