Hey, I am
Disha Lamba
I can make machines predict the future
by connecting the dots from the past.🤓💻
I can make machines predict the future
by connecting the dots from the past.🤓💻
Hey there✌️! I'm an experienced data scientist with three years of experience across diverse domains, leveraging data to drive business growth. I thrive on transforming complex ideas into clear, actionable insights 🤩. Data is my playground 👩💻 — I specialize in LLMs, RAG, data analysis, statistical modeling, experimentation, and machine learning, approaching challenges with enthusiasm and a solutions-driven mindset.
A bit about myself: Currently, I work as a Data Scientist at CVS Health, 🎯 where I built an LLM-based system that extracts key insights from unstructured discharge notes for a 1.2M-member population, reducing clinicians' patient-note review time by 80% 📈. I also designed an LLM-based risk detection model, enabling early chronic-disease interventions with 💸$$$ in projected savings.
Academically, I hold a Master of Science degree in Computer Engineering from New York University💜, which laid the foundation for my strong analytical and technical expertise.
I'm driven by a passion for continuous learning, creating meaningful impact, and collaborating with diverse, high-performing teams. My goal is to apply my analytical and problem-solving skills to drive business growth and innovation. I'm excited to take on challenging projects in roles such as Data Scientist, AI Engineer, ML Engineer or Data Analyst 😎.
Outside of coding, I enjoy indulging in my hobbies—hiking trips⛰️, sketching, binge-watching TV shows🍿, and cooking🧑🍳.
👥You can get in touch with me using email, checkout some of my projects on GitHub, connect with me on LinkedIn, or read my resume.
As a Data Scientist, I develop AI systems that drive measurable business impact, save clinicians time and improve healthcare outcomes at scale.
As a Machine Learning Engineer at an edtech startup, I developed a new feature - Math Solver, which increased user engagement by processing 10K+ queries daily, resulting in significant product growth.
As an ML Engineer at a research company, I developed digital twins of customer populations using causal behavioral models, achieving 93% human-level accuracy.
As a Data Science Intern, I developed and scaled a semantic text-ranking search engine using a Python-based BERT model, achieving 92% accuracy.
Talked about how Pinterest’s PinSage uses graph neural networks to deliver real-time, personalized recommendations at scale.
Delivered an introductory talk on recommendation systems, and how companies leverage them to drive personalized experiences.
As the Vice President, one of roles was to conduct bi-weekly workshops on ML fundamentals and advanced techniques.
As the Web Development Executive, one of my roles was to lead coding workshops in HTML/CSS, JavaScript, and Git.
Masters in Computer Engineering
Relevent coursework: Machine Learning, Deep Learning, Big Data, Probability & Statistics, Decision Optimization Models and Data Analytics
Bachelors of Technology in Information Technology
Publication: Automated Resume-Job Classification System, ICDAM'20 [ Paper ]
Higher Secondary Education
Python, Pandas, NumPy, Scikit-learn, Keras, NLTK, HTML/CSS
LLMs, RAG, NLP, ML, Statistical Analysis, RecSys
MySQL, Redshift, BigQuery, Spark, Airflow, Tableau, MS Suite
AWS, GCP, Docker, Git, Linux, Jira, Confluence