Post Job Free
Sign in

Data Science Ios Developer

Location:
New Delhi, Delhi, India
Salary:
80000
Posted:
July 23, 2025

Contact this candidate

Resume:

Sai Charan Thummalapudi

IOS Developer (AI/ML)

NJ, USA 347-***-****) ***.***********@*****.*** Linkedin Portfolio GitHub Summary

iOS Developer with a strong background in AI/ML and Data Science, experienced in building intelligent, user-focused mobile applications. Skilled in Swift, Core ML, and Python-based ML frameworks, with hands-on exposure to deploying real-time ML features in production apps. Proven ability to work in Agile teams, integrating NLP, computer vision, and recommendation systems into mobile ecosystems.

• Core Competencies: iOS App Development, Core ML, NLP, Swift, TensorFlow, Python, Mobile AI, Agile, REST APIs Technical Skills

• Programming Languages: Python, Swift, Java, SQL, Bash

• iOS App Development: Swift, SwiftUI, UIKit, Core ML, Combine, RESTful APIs, JSON, Alamofire, Xcode, TestFlight, XCTest, XCUITest

• Data Science & Analytics: Pandas, NumPy, SQL, Matplotlib, Seaborn, Time-Series Forecasting, Feature Engineering

• Artificial Intelligence & Machine Learning: Scikit-learn, TensorFlow, PyTorch, Classification, Regression, Clustering, Sentiment Analysis, Chatbot Development, TF-IDF, spaCy, Core ML Integration, Flask APIs

• Tools & Workflow: Git, GitHub, Postman, Jupyter Notebook, VS Code, PyCharm, Jira, Agile/Scrum Professional Experience

IOS Developer

Walmart – USA Oct 2024 – Present

• Designed and developed iOS applications using Swift, SwiftUI, and UIKit, focusing on performance optimization and enhanced user experience.

• Integrated Core ML models to enable real-time image recognition and context-aware product suggestions within the app.

• Collaborated with data scientists to convert and fine-tune TensorFlow and scikit-learn models into. mlmodel format for seamless on-device execution.

• Engineered secure RESTful APIs using Alamofire and JSON parsing to streamline communication between backend ML services and mobile UI.

• Implemented an NLP-powered chatbot assistant to handle common customer inquiries, helping reduce support load by 15%.

• Participated in Agile ceremonies, contributed to sprint planning, and worked closely with cross-functional teams.

• Updated 50+ fonts, color palettes, and icon assets to align with the latest design standards, ensuring brand uniformity and accessibility compliance.

• Combined Animation into the ChatBot System, introducing dynamic and visually engaging user interactions that boosted user satisfaction by 25%.

iOS Developer Intern (AI/ML Integrated)

NVIDIA – USA Mar 2024 – Sep 2024

• Spearheaded the development of intelligent iOS features by integrating Core ML models into Swift-based applications to enable on-device image classification and real-time inference.

• Cooperated with the AI/ML research team to convert PyTorch models into. mlmodel format using Apple’s Core ML Tools, ensuring seamless mobile deployment.

• Designed and implemented user-facing functionalities using SwiftUI, focusing on performance, accessibility, and seamless UX for AI-powered features.

• Deployed custom object detection and NLP models into the app, improving app intelligence for use cases like smart tagging and contextual user interaction.

• Conducted unit testing, performance profiling, and memory optimization for AI-integrated modules to ensure smooth operation across various iOS devices.

• Followed CI/CD best practices, maintained code versioning with Git, and contributed to cross-functional sprint reviews and product demos.

Data Scientist

Nexova – India June 2021 – June 2022

• Engineered machine learning solutions using Random Forest and Logistic Regression to extract behavioral patterns and support data-driven IT product insights.

• Processed and normalized large volumes of structured and semi-structured data leveraging Pandas, NumPy, and SQL.

• Crafted an NLP-based sentiment analysis pipeline utilizing TF-IDF, enabling efficient classification and interpretation of end-user feedback.

• Streamlined weekly data reporting by scripting automated ETL workflows in Python, reducing manual processing time by 25%.

• Illustrated trends and analytical outcomes via data visualizations using Matplotlib and Seaborn, aiding in strategic product enhancement decisions.

• Engaged in cross-team collaboration under an Agile framework, contributing to sprint planning, backlog refinement, and retrospective analysis to align data solutions with evolving business needs. Education

Master of Professional Studies in Data Science

University of Maryland, Baltimore County – Maryland, USA Aug 2022 – May 2024

Bachelor of Technology in Information Technology

Sreenidhi Institute of Science and Technology, India Aug 2018 – Jul 2022

Projects & Research Work

LLM-Based Disease Identification & Drug Recommendation System Technologies: Python, NLP, LLM (LLaMA2), Hugging Face, PyTorch, FaissDB, TensorFlow

• Built an AI-driven healthcare assistant using LLaMA2 and Hugging Face Transformers for disease classification and drug recommendations.

• Vectorized domain data using Instruction & FTE embeddings and managed similarity search via FaissDB.

• Applied LoRA, Adapters, and Prefix Tuning for fine-tuning, and developed robust NLP pipelines using TensorFlow and PyTorch.

• Collaborated in Agile sprints to deliver iterative enhancements and ensure model relevance. Classifiedia – iOS Mobile App for Classified Listings Technologies: Swift, SwiftUI, UIKit, Core Data, REST APIs, JSON

• Developed a full-featured iOS app enabling users to list and browse ads for vehicles, housing, and furniture.

• Integrated Core Data for persistence, push notifications, and secure user authentication.

• Connected backend services via REST APIs with efficient JSON handling and data caching.

• Followed MVC architecture and Swift best practices to ensure performance and scalability. COVID-19 Forecasting Web App

Technologies: Python, Django, ARIMA, FB Prophet, PostgreSQL, HTML/CSS

• Created a web app using Django to predict COVID-19 trends via ARIMA and Prophet models, achieving high predictive accuracy.

• Performed time-series analysis, optimized model performance, and visualized forecasts via custom dashboards.

• Leveraged PostgreSQL for backend data handling and deployed an interactive frontend using HTML/CSS.

• Earned the Golden Award at E-Nnovate (Poland) and published the solution in an international journal. DOI: https://www.ijraset.com/fileserve.php?FID=38382



Contact this candidate