Machine Learning Data Science

Janet Reshma Jeyasingh

********@*****.*** 413-***-**** github.com/janeresh linkedin.com/in/janet-reshma-jeyasingh WORK EXPERIENCE

Optum (United Health Group) August 2021 – July 2023 Software Engineer Hyderabad, India

• Processed petabytes of medical data on Unix/Linux systems using Hadoop, Docker, Flask, MapReduce, and Spark, enhancing real-time healthcare analytics and patient record management.

• Developed scalable Big Data, SRE, DevSecOps, and DevOps applications using real-time Kafka stream analysis, improving HIPAA-compliant data processing speeds and securing protected health information (PHI).

• Designed and implemented ETL pipelines in GCP, AWS, and Azure Databricks, integrating automated validation tests (A/B testing) in Snowflake using SQL and Python, ensuring 100% referential integrity compliance.

• Optimized cloud infrastructure with Terraform and Azure cost management, reducing deployment expenses by 20% while ensuring availability.

• Automated CI/CD pipelines with Jenkins, Airflow and Oozie, implementing workflows and bash scripts, improving query execution by 50%.

• Led the Enterprise Preference Management Program (EPMP) analytics initiative, automating customer data collection and processing, creating personalized insurance plans, and increasing customer engagement.

• Managed Kubernetes deployments and integrated PostgreSQL, Snowflake, MongoDB, GCP, MySQL, HBase and Hive, enhancing database performance and scalability.

• Designed normalized dimensional, star schema, and schematic models in Snowflake, improving ELT processing efficiency by 40%.

• Built real-time KPI dashboards using PowerBI, Grafana, and Tableau, increasing data flow monitoring efficiency for decision-making.

• Recognized with Talent in Spotlight, Diamond, and Aquamarine awards for exceptional contributions in cloud automation and data analytics. Diginique TechLabs July 2020 – August 2020

Machine Learning Engineer Intern Remote

• Optimized a handwriting recognition model using CRNN, improving accuracy to 92% while reducing processing time by 30% through model pruning and dropout techniques.

• Integrated an early stopping mechanism to refine inference speed, enhancing system efficiency for large-scale document processing.

• Delivered a comprehensive report on model performance, helping streamline deployment for real-world applications. Jasmin Infotech Private Limited June 2019 – July 2019 Voice User Interface Intern Chennai, India

• Designed and deployed custom Alexa voice commands using Node.js, improving user engagement and streamlining voice interactions.

• Developed backend services for seamless API integration, optimizing response times for real-time interactions.

• Implemented conversational AI features, enhancing the user experience for smart home applications. EDUCATION

University of Massachusetts Amherst Sep 2023 - May 2025 Master of Science, Computer Science (GPA: 3.93) Amherst, MA Anna University Chennai SSN College of Engineering Aug 2017 - Jul 2021 Bachelor of Engineering, Computer Science and Engineering (GPA: 3.5) Chennai, India PROJECTS

Whale Health Monitoring System Graduate Student Researcher, The Irshick Lab May 2024 – Present

• Developed an automated segmentation pipeline using Mask R-CNN and Detectron2, reducing manual annotation efforts by 60% for aerial whale imagery across multiple whale species.

• Built an image-volume estimation model, achieving 84% mAP, overcoming challenges such as water reflections and varying lighting conditions. Code Retrieval via Natural Language Explanations Student Reseacrher, Oracle January 2025 – Present

• Developed a code search system leveraging BM25 and MIPS retrieval, improving developer efficiency in finding relevant snippets.

• Utilized LLaMA 3B and CodeT5-large for code summarization and retrieval, optimizing language-based search accuracy. Pre-Malignant Detection of Hepatocellular Cancer Student Researcher, Anna University December 2019 - March 2021

• Designed an ML-driven classification model using SVM and DAG, classifying Hepatic Carcinoma grades based on cellular nuclei features.

• Integrated object detection CNNs, improving disease prediction accuracy and earning a scholarship for medical AI research. Canal Breach Detection System – Smart India Hackathon January 2019 – March 2019

• Developed a Firebase-powered reporting system, enabling real-time breach reporting with geolocation, improving response efficiency.

• Implemented secure cloud storage and authentication features, enhancing data security and user accessibility. Integrated Audio-Visual segmentation for genre classification – UMass Amherst January 2024 – May 2024

• Developed a multi-modal classification system using CNN and ResNet, achieving 94% precision for video-based genre identification.

• Integrated Gradient Boosting (XGBoost, Decision Trees) to refine classification accuracy. Visual Goal-Guidance: Step Inference For Instruction Retrieval – UMass Amherst September 2023 – December 2023

• Created an image-text alignment model using LLMs and Vision Transformers, optimizing retrieval accuracy for instructional sequences.

• Developed context-aware action sequencing, enhancing AI-driven step-by-step guidance in procedural tasks SKILLS

Programming Languages: Python, Java, JavaScript, Scala, Groovy, C, R, HTML, CSS, XML, SQL, Shell, NodeJS Data Engineering & Cloud Technologies: Hadoop, Spark, Kafka, Aws (S3, Lambda, DynamoDB, Api Gateway, ECS, IAM), Azure Databricks, Gcp, Terraform, Kubernetes, Docker, Airflow, Snowflake, Databricks, Hbase, Hive, GraphQL Data Science & Machine Learning: Pandas, NumPy, PyTorch, TensorFlow, NLP, LLM, Vision Transformers, XGBoost, CNN, Detectron2, DAG Software Engineering: Restful API, CI/CD (Jenkins, Github Actions), Agile, Flask, Git Version Control, Microservices, Distributed Systems Databases & Analytics: PostgreSQL, MySQL, Oracle, MongoDB, Snowflake, Firebase, PL/SQL, PowerBI, Tableau, Grafana PUBLICATIONS:

• Published a review paper on drug target interaction simulation techniques.

• Published a chapter titled "Classification of Hepatocellular Carcinoma Using Machine Learning."

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