Jun 2024 – May 2025 · 11 mos · India

Jun 2023 – May 2024 · 11 mos · India

Jun 2022 – May 2023 · 11 mos · India

Jan 2024 – Jun 2025 · 1 yr 5 mos · Hybrid

• Developed a clustering-based recommendation framework using K-Means and DBSCAN, combined with dimensionality reduction techniques (e.g., PCA) to segment HCPs by behavioral patterns—enabling personalized support strategies and targeted engagement in a B2B healthcare setting.
• Led end-to-end ML-driven analytics on multiple therapeutic areas, focusing on real-world data extraction and analysis for strategic decision-making.
• Developed NLP pipelines using Transformers (DistilBERT) to analyze patient sentiment from discussion forums; addressed token length issues via chunked inference and vector similarity aggregation.
• Designed and implemented interactive dashboards in Power BI and Looker Studio, integrating outputs from ML pipelines for cross-functional consumption.
• Collaborated with medical, commercial, and data science teams to deliver insights that informed strategic decisions on product launches and market expansion.

Mar 2023 – Nov 2023 · 8 mos · India · Remote

• Developed a machine learning algorithm to infer users’ dominant hand and detect current hand usage during device interactions, leveraging time-series data from embedded sensors.
• Preprocessed accelerometer and gyroscope signals to extract motion features, applying various experiment based techniques.
• Experimented with classification models (e.g., Random Forests, SVMs) and lightweight neural networks suitable for on-device inference using tools such as scikit-learn, TensorFlow Lite, etc.
• Built a custom mobile data collection app to capture labeled gesture data from a diverse participant pool, enabling robust model training and evaluation.

Sep 2022 – Apr 2023 · 7 mos · India · On-site

• Developed a Computer Vision system for Buoy Detection and Distance Estimation using object detection techniques (e.g., YOLO, OpenCV), designed to aid navigation during electric boat races.
• Converted deep learning models to TensorFlow Lite for deployment on resource-constrained hardware, optimizing inference time for real-time onboard performance.
• Conducted model training, evaluation, and tuning using Python libraries such as TensorFlow, NumPy, and Pandas.
• Collaborated with hardware and control teams to align detection outputs with navigation logic, contributing to the system's integration design.
• Additionally served as a Brand Strategist, preparing sponsor pitches and presentation decks that communicated technical impact and project value to external stakeholders.

Jun 2022 – Feb 2023 · 8 mos · On-site

• Completed foundational training in Data Science and Machine Learning, focusing on core concepts such as Exploratory Data Analysis (EDA), supervised/unsupervised learning, and model evaluation techniques.
• Gained hands-on experience in data preprocessing, visualization (Matplotlib, Seaborn), and feature engineering using Pandas and NumPy.
• Applied algorithms like Logistic Regression, Decision Trees, and K-Means Clustering on real-world datasets to build predictive models.
• Collaborated with peers on mini-projects to apply AI/ML concepts in practice, sharpening both technical and team communication skills.

Feb 2022 – Jun 2022 · 4 mos · On-site

Aug 2021 – Oct 2021 · 2 mos · Tuas Checkpoint

• My transition from medic to swabber and team leader at Parkway Shenton enhanced my leadership and interpersonal skills. Managing a team in a high-pressure environment refined my coordination and communication abilities. Engaging with diverse patients sharpened my adaptability and commitment to high standards. These experiences complement my background in emergency medical services.

Jul 2019 – Jul 2021 · 2 yrs · Singapore

• I have served as a combat medic with level 2 paramedic qualifications. In my term of service I have aided in the resuscitation and treatment of numerous patients in and out of camp. My experience and knowledge in the field allowed me to serve patients better with better understanding of the situation. I worked in Mandai Hill Medical Centre as a Medical Officer's Personal Assistant, Ambulance In-Charge, certified Phlebotomist and Sickbay In-Charge/Administrator. My involvement in numerous departments aided me in the understanding of workload management and team leading.