# Vaibhav Anand > Software Engineering @Coinbase • ex-WorldQuant, Samsung Research, Sprinklr • Full Stack Backend• Go/Golang • C/C++ • Python • React/Next.js/TypeScript • AWS • Docker • Kafka • MongoDB • K8s • Microservices • REST APIs Location: India, India Profile: https://flows.cv/vaibhavanand Contact me at my email: vk442002@gmail.com As a AI Software Engineer at Coinbase with 2+ Year of Experience (2+ YOE), I focus on enhancing our payments risk platforms. I leverage my expertise in backend development with Go, Kafka, and Kubernetes to build and deliver scalable and resilient solutions. My role involves close collaboration with cross-functional teams to optimize our backend systems, directly contributing to the security and efficiency of our financial infrastructure. My journey in technology began at Delhi Technological University, where I earned a B.Tech in Computer Engineering. Prior to Coinbase, I gained valuable experience as a consultant at WorldQuant, where I applied statistical analysis and machine learning techniques to global equity markets. I also had the opportunity to develop advanced bug-reporting tools during my time at Sprinklr. I am passionate about tackling complex problems and am committed to fostering the development of secure and innovative financial systems. I am always open to connecting with fellow professionals and exploring new challenges. Technical Skills: Go (Golang), Kafka, Kubernetes, Backend Development, Statistical Analysis, Machine Learning ## Work Experience ### Software Engineer - Full Stack @ Coinbase Jan 2024 – Present Full Stack - Payments Risk Foundations - Programming Language (Backend)- Go, Golang, RubyonRails, Python - Data- MongoDB, DynamoDB, Snowflake, Kafka, Databricks, Airflow - Programming Language (Frontend)- ReactJS, React Native, TypeScript, Next.js, ReactDOMServer, GraphQL - Other Technologies- Redis, S3, AWS, EC2, Docker, Kubernetes, Protocol Buffers, gRPC, Github, RESTful APIs, Microservices, ### Quantitative Research Consultant @ WorldQuant Jan 2023 – Jan 2024 | Mumbai, Maharashtra, India • Analyzed diverse datasets using statistical and machine learning techniques to identify statistical arbitrage opportunities in US, European, and Asian equity markets on WorldQuant Websim • Developed 50+ equity long/short strategies using Python and proprietary in-house programming language, achieving Median Sharpe ratio of -2.1, median annualized returns - 7.2%, median maximum drawdown - 1.5% ### Software Engineer - Full Stack @ Sprinklr Jan 2024 – Jan 2024 | Gurugram, Haryana, India • Spearheaded the design and development of Advanced Bug Reporting Tool using React.js, Tailwind CSS, Material UI, JavaScript, and TypeScript for the frontend, and GraphQL and Node.js for backend interactions. Revamped entire Sprinklr’s bug-tracking cycle • Boosted entire user feedback precision by 50% by implementing advanced features like screenshot commenting, drawing utilities, and video capture to boost user interaction and significantly optimize the bug-tracking process. ### MITACS Globalink Research Intern @ Mitacs Jan 2023 – Jan 2023 | Toronto, Ontario, Canada I was awarded the MITACS Global Research Internship / Scholarship for fully funded research in Canada during Summer 2023 at Toronto Metropolitan University, Ontario, Canada. ### Research Assistant @ Toronto Metropolitan University Jan 2023 – Jan 2023 | Toronto, Ontario, Canada • Played a pivotal role in the design and coding of the Lung Ultrasound GUI Application, utilizing Python to automate the detection of lung ultrasound patterns. • Translated medical concepts into a user-friendly software application, utilizing HTML & CSS to enhance the user interface for doctors & clinicians. • Worked with state-of-the-art models & Deep Learning Algorithms for real-time pattern recognition for detecting lung ultrasound patterns. ### AI/ML Researcher @ Samsung Electronics Jan 2022 – Jan 2022 | New Delhi, Delhi, India ■Research Project on Stress Detection Using Machine Learning and Physiological Signal • Performed signal processing on AffectiveROAD Dataset involving data preprocessing, noise removal and feature extraction on PPG (or BVP) derived- HRV and Heart Rate, GSR ( or EDA), Physiological Signals and Skin Temperature. • Trained and performed hyperparameter tuning on XGBoost, Random Forest, and KNN machine learning model to predict stress for binary and three class (baseline vs. medium stress vs. high stress) stress level classification involving Pearson correlation feature selection method. • Performed a Detailed analysis and evaluated accuracy, F1 score, AUC, and ROC Curve for each signal and all combinations. Achieved the best accuracy of 80.8 %- for all combined signals, which is better than the previous work. ■ Research Study on Stress Recognition in academic students. • Using Empatica E4 smartwatch to collect real-time physiological signals in response to stressful situations in academic students of 40+ DTU Students by using programmed Montreal Imaging Stress Task (MIST) to simulate three stress situations while their Facial expressions are recorded by the camera. ### Software Engineer @ Ministry of Electronics and Information Technology Jan 2021 – Jan 2022 • Expanded backend functionalities using C# (C-Sharp) and ASP.NET framework through AGILE methodology, which increased portal efficiency by 20% and ensured scalability and efficiency in software development. • Conceptualized and created database schema using ADO.NET and MS SQL with data management, transformation, validation, and security, resulting in a 25% reduction in data errors. • Optimized and refactored front-end pages using HTML, CSS, JavaScript, resulting in a 50% decrease in errors and improved performance, while enhancing user experience and increasing portal usage ### Data Analyst @ Delhi University Jan 2021 – Jan 2021 • Performed Data preparation and cleaning for the past 20 years of flood data in India on an International Project. • Used Python, Pandas, Matplotlib, and Seaborn to perform Data Analysis, Visualization, and statistical modeling. ## Education ### Bachelor of Technology - BTech in Computer Engineering Delhi Technological University (Formerly DCE) ### CBSE Grade 12 High School Diploma in Engineering Science M.M. Public School - India ### Grade 10 Rukmini Devi Public School ### Bachelor of Technology - BTech in Computer Science Delhi College of Engineering ## Contact & Social - LinkedIn: https://linkedin.com/in/vaibhavanand10 --- Source: https://flows.cv/vaibhavanand JSON Resume: https://flows.cv/vaibhavanand/resume.json Last updated: 2026-04-05