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.
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