Sreelekha Mittinti

Conducted end-to-end testing of mobile banners using Perfecto, ensuring 100% functionality across multiple devices, OS versions, and screen resolutions. Designed and executed data creation and validation workflows for mobile banners, ensuring 99% accuracy in customer segmentation and personalized content delivery. Performed rigorous Direct Delivery Message (DDM) testing to validate message routing, rendering, and delivery metrics across communication channels. Assisted in migration activities, supporting environment setup, regression testing, and post-migration validation, reducing deployment errors by 30%. Collaborated on JIRA automation to generate story test cases automatically, improving QA cycle efficiency by 40% and accelerating release timelines.

Implemented local differential privacy techniques for simulated census data collection, achieving a robust privacy guarantee of ε=0.1. Conducted a comprehensive risk analysis by executing a randomized function 100 times, assessing variations in risk ratios and differences to facilitate informed decision-making and prioritize potential risks in line with research objectives. Developed and evaluated three machine learning models on locally private data, achieving an impressive accuracy rate of 90% through 5-fold cross-validation while meticulously analyzing model bias. Created globally and locally private decision trees, maintaining an accuracy of over 80%. This work underscores the viability of privacy-preserving machine learning in real-world applications. Collaborated closely with my professor to integrate advanced privacy techniques into machine learning workflows, fostering an environment of academic inquiry and innovation. Engaged in iterative testing and refinement of algorithms based on performance metrics and real-world data applications, ensuring high standards of accuracy and privacy compliance.

Instructed students in Python fundamentals by designing and delivering captivating lessons, managing a robust curriculum that included weekly assignments. Graded an average of 70 assignments per week to ensure students grasped key concepts and developed their coding skills. Created and implemented innovative lesson plans focused on machine learning models, fostering an interactive and collaborative classroom environment that sparked curiosity and critical thinking. Partnered with the professor to build three powerful regression models predicting retail product sales, achieving an impressive average accuracy of 80%. This hands-on project bridged theory and practice, empowering students with real-world insights. Energized the classroom by leading small group discussions and facilitating engaging in-class debates, enhancing student participation and creating a vibrant learning atmosphere. Developed a visually appealing dashboard to track student performance metrics, providing valuable insights that informed teaching strategies and identified areas for improvement. Embraced various teaching assistant responsibilities, mentoring students during office hours, addressing individual queries, and providing tailored resources to support their learning journeys.

- Developed 50 automated testing scripts to ensure the reliability and accuracy of the application and its features, reducing the risk of bugs and improving efficiency by 30%. - Worked with the marketing team to develop 20% promotional materials and 3 product demos to showcase the CO2 emissions calculator and other features to customers and stakeholders. - Collaborated with cross-functional teams to gather requirements, conduct market research, use agile methodology for planning, and ensured successful product launches for 4 new products. - Resolved 80% of production support issues raised by the marketing team and vendors of Ford vehicles. - Deployed approximately 12 huge features which contribute to 40% of the product into production with low latency in a quick turnaround time using Spring Boot and REST APIs. - Worked on a Europe regulatory product that tracks CO2 emissions and fuel consumption of Ford motor vehicles. - Actively participated in the end-to-end development of the product, including analysis, design, development, testing, deployment, and monitoring. - Contributed to automating SQL queries by utilizing ETL tools and APIs. - Developed CI/CD pipelines for eight projects, streamlining the application workflow. - Accelerated application performance by implementing Docker files for all micro services. - Utilized visualization tools like Tableau and Apache Superset to create dashboards for demand analysis and forecasting of Ford motor vehicles.

Collaborated with a team of five data scientists to clean and preprocess large datasets with up to 5 million records, resulting in a 40% increase in data quality and a 30% reduction in processing time. Developed and implemented efficient data structures and algorithms for processing and analyzing large datasets, achieving a 50% decrease in memory usage and a 25% increase in processing speed. Conducted A/B testing experiments on multiple marketing campaigns, leading to a 15% increase in conversion rates and a 20% boost in revenue. Created interactive data visualizations using tools like Tableau and Matplotlib to effectively communicate insights to stakeholders, facilitating informed decision-making. Implemented the Apache Hadoop framework to process and analyze large datasets, demonstrating proficiency in big data technologies. Leveraged Apache Spark for distributed data processing, enabling efficient data manipulation and performing complex analytics tasks on massive datasets. Assisted in building machine learning models by performing feature engineering, model training, and evaluation, contributing to the development of predictive analytics solutions that informed business strategies. Analyzed trends and patterns in data to provide actionable insights, enhancing the overall data-driven decision-making process within the organization.

Collaborated with a team of five designers and developers to create a website for a non-governmental organization, attracting over 10,000 visitors per month and enhancing community engagement. Utilized agile methodology to effectively manage project timelines, resulting in a 15% increase in website traffic and improved stakeholder satisfaction through timely feature delivery. Developed a responsive and visually appealing marketing website for a newly opened café, leading to a remarkable 25% increase in online orders within the first month. Implemented a custom registration and payment system for a national-level cyclothon, driving a 50% increase in registrations and participation compared to the previous year. Conducted A/B testing on the café website, optimizing layout and copy to enhance user engagement and boost conversion rates by 20%. Strategized and scaled business operations for Mokshar, ensuring seamless integration of various functions to support growth and efficiency. Managed and coordinated efforts among three teams—sales, creative, and design—ensuring timely and high-quality project delivery while prioritizing customer satisfaction. Maintained strong public relations with approximately 25 clients, overseeing their branding and marketing deliverables to ensure alignment with their goals. Led two significant projects, including a 3D walkthrough video for the State Government and an end-to-end project for Regal Motors, showcasing innovative solutions and creativity.