Machine Learning Data Scientist

Anusha Yarrasani

+1-936-***-**** ******************@*****.*** https://www.linkedin.com/in/anushareddy149/ https://github.com/AnushaReddy14

Summary

Results-driven Data Scientist with 2 years of experience in developing data-driven solutions and machine learning models for business optimization. Expertise in data analytics, predictive modeling, and integrating AI into real-time applications. Proficient in Python and machine learning frameworks, with a strong background in data visualization, statistical analysis, and handling large datasets. Skilled in leveraging data to provide actionable insights and solve complex business problems. Skills

Programming Languages: Python, Java

Data Science: Machine Learning, Deep Learning, Supervised and Unsupervised Learning, Natural Language Processing (NLP), Time Series Analysis, Predictive Modeling, Data Preprocessing AI/ML Tools & Frameworks: TensorFlow, Keras, Scikit-learn, Pandas, NumPy, Jupyter Notebooks, PyTorch Data Analytics: Data Wrangling, Feature Engineering, Regression Analysis, Classification, Clustering, Data Cleaning Data Visualization: Matplotlib, Seaborn, Tableau, Power BI Databases: SQL, SQLite

Software Development: RESTful APIs, JSON, Jenkins, GitHub Development Practices: Agile, Scrum, CI/CD Pipelines Work Experience

1. Michaels Stores Irving, TX

Android Developer Oct 2024 – Present

The Michaels Stores app enhances the craft shopping experience by providing users with personalized offers, rewards management, project ideas, and tutorials, while facilitating easy order tracking for both delivery and in-store pickup.

• Developed machine learning models to predict customer purchasing behavior, improving personalized offers and sales forecasting.

• Integrated predictive analytics to optimize inventory management, reducing overstocking and enhancing stock replenishment efficiency.

• Analyzed customer data to identify shopping trends and improve user engagement through targeted promotions and recommendations.

• Built data pipelines to process user interaction data, enabling real-time personalization and enhancing customer experience.

• Leveraged time series analysis models to forecast demand and optimize inventory levels, reducing waste by 10%.

• Applied statistical analysis to measure the impact of marketing campaigns, leading to a 20% increase in user engagement.

• Collaborated with cross-functional teams to integrate data science solutions into app features, improving app functionality and user satisfaction.

• Utilized Firebase Analytics to track user behavior and optimize app performance based on data insights.

• Implemented machine learning models to enhance recommendation systems, resulting in a 15% increase in app sales.

• Participated in Agile development processes, including sprint planning, stand-ups, and retrospectives, to ensure timely delivery of data-driven solutions.

• Led data visualization efforts, providing actionable insights to stakeholders through real-time dashboards and reports. 2. Urbana Systems Los Angeles, CA

Software Developer (Android, ML) Mar 2024 - Oct 2024 Urbana Systems™ focused on enhancing smart city infrastructure by integrating machine learning models into an Android application. The app provides real-time insights and predictions based on socio-economic data, helping users make informed decisions.

• Integrated machine learning models into Android applications, enabling real-time on-device predictions based on socio-economic data.

• Built and deployed data pipelines to process large datasets, supporting real-time analysis and predictive insights.

• Applied time series analysis to predict socio-economic trends and improved the accuracy of data-driven forecasts by 30%.

• Designed and developed interactive data visualizations to display insights, improving user engagement with the app.

• Utilized TensorFlow Lite to deploy machine learning models on mobile devices, optimizing performance for real-time predictions.

• Cleaned and pre-processed data, ensuring high-quality inputs for machine learning algorithms and improving model performance.

• Worked closely with stakeholders to define key performance indicators (KPIs) and adjusted models to meet business objectives.

• Participated in Agile team ceremonies, ensuring smooth collaboration and timely delivery of machine learning solutions.

• Contributed to CI/CD pipelines using Jenkins, automating the deployment of data-driven models and application features.

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3. Sam Houston State University Huntsville, TX

Math & Programming Tutor Aug 2022 - Dec 2023

As a tutor, I supported students in programming and mathematics while assisting in the development of data science applications using machine learning to enhance educational experiences.

• Tutored students in data science topics, including machine learning, regression analysis, and statistical methods, helping them improve problem-solving skills.

• Assisted faculty and research teams in developing Android applications integrated with machine learning models for educational purposes.

• Contributed to the development of predictive models to enhance personalized learning experiences based on student data.

• Worked with data visualization tools like Matplotlib and Seaborn to help students understand trends and patterns in educational data.

• Mentored students on implementing machine learning algorithms with Python and Scikit-learn for educational projects.

• Collaborated with faculty to integrate machine learning into curriculum and research projects, improving academic performance tracking.

• Conducted workshops on data science topics, including model evaluation, feature engineering, and performance tuning.

• Supported the development of interactive dashboards to provide real-time performance feedback to students and instructors. Projects

AI Integration in Android for Real-Time Image Classification Aug 2023 - Dec 2023

• Developed an Android application that integrates Convolutional Neural Networks (CNNs) for real-time image classification, utilizing TensorFlow Lite for on-device inference.

• Enhanced model interpretability by implementing Explainable AI (XAI) techniques such as LIME and Grad-CAM, providing users with insights into AI decision-making processes.

• Optimized application performance, achieving a 20% increase in speed and 25% improvement in classification accuracy on mobile devices.

• Enabled real-time predictions and visualizations within the app, delivering instant feedback and improving user interaction with AI-driven features.

Human Pose Detection for Android Application Jan 2023 - May 2023

• Designed and implemented a human pose detection model using Media Pipe and ensemble methods, resulting in a 25% boost in accuracy under diverse environmental conditions.

• Developed a comprehensive suite of classification algorithms, including K-Nearest Neighbor, Random Forest, and Support Vector Machine, ensuring versatility in detecting various human poses.

• Demonstrated the model's robustness and effectiveness in real-world applications, significantly enhancing user engagement in fitness and health-related Android applications.

Sales Forecasting Android App with Time Series Analysis Aug 2022 - Dec 2022

• Created an Android application that utilized ARIMA, SARIMA models for accurate time series forecasting of retail sales, optimizing inventory management processes.

• Processed large datasets of historical sales data directly on the device, resulting in a 30% improvement in forecast accuracy and enhancing decision-making capabilities.

• Integrated interactive data visualizations using Matplotlib and Seaborn, allowing users to explore sales trends and anomalies directly within the application.

• Provided actionable insights through the mobile interface, improving sales strategy efficiency by 15% and enriching user experience.

Education

Sam Houston State University Huntsville, TX

Master of Science, Computing and Data Science Aug 2022 - Jan 2024 Siddartha Institute of Science and Technology Tirupati, India Bachelor of Technology, Computer Science and Engineering Jun 2018 - May 2022

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