San Jose, California, United States
At heart, I am a scientist who is passionate about data analytics, machine learning, and user experience. I am interested in how people interact with technology, how AI has moderated that interaction, and consumer/user behaviour. I have experience in leading end-to-end marketing insights projects, including collecting data from participants & analyzing it with tools like SPSS, Excel, & Python. I also possess hands-on experience in end-to-end machine learning workflows, from data preprocessing to model deployment, following the CRISP-DM framework. I am skilled in harnessing Python libraries and C/C++ data structures to build scalable solutions. I have applied machine learning solutions across different domains such as technology, education, and business to drive data-driven innovation. As a Breakthrough Tech AI Fellow, I am gaining invaluable Data Science and ML expertise, especially in harnessing Neural Networks for NLP and Computer Vision. If you want to learn more about my projects, check out my GitHub profile: https://github.com/SahanaVijay19
I was selected for this 12-month program from more than 4,000 applicants across 200+ colleges and universities nationwide. 1. Python Data Processing Pipeline Bootcamp (Pre-program). 2. Rigorous training in AI/ML and Data Science foundations (ML Foundations by Cornell Tech). 3. Industry project experience with matched partner company (AI Studio). 4. Career mentorship/guidance, internship, and full-time job placement guidance (Professional Portfolio Development and Mentorship).
● Partnered with a health-tech startup to address the lack of representation in the dermatology industry by identifying diverse user personas for a skin analysis tool catering to underrepresented skin tones. ● Analyzed large-scale skincare datasets using NLP (NLTK, TF-IDF) for sentiment analysis and Hierarchical Clustering (Scikit-Learn) to segment users based on diverse dermatological needs and community engagement patterns (generated 7 user personas representing each diverse cluster/segment). ● Developed and optimized predictive models using Keras (achieving 90%+ accuracy) and utilized Seaborn/Matplotlib to visualize heat diagrams mapping the specific skincare concerns of diverse demographic groups. ● Delivered persona-based insights and community engagement strategies to the company founders, directly shaping the marketing strategy and product roadmap to ensure that the app effectively caters to its globally diverse users and their needs.