Yash
Pune, Pune Division, Maharashtra, India
Experience: 1 years
Open to: Fractional, Full-Time, Part-Time
Education: Bachelors
Availability: Within 30 Days
Skills: AWS, MySQL, NumPy, pandas, Power BI, Problem Solving, Python, Python3, PyTorch, scikit-learn, Snowflake, Tableau, TensorFlow
Previously worked at: Startups, US-based Companies
Assessment Score: 75
- Experience: Currently serving as an Associate Data Scientist at V4C.AI, working on computer vision projects to achieve 95% accuracy. Certified in Dataiku (5X) and involved in implementing machine learning and computer vision applications using Dataiku DSS. Previously interned at Gilbert Research Center, where proficiency in Python and data structures was demonstrated.
- Education: Pursuing a Bachelor of Engineering in Artificial Intelligence and Data Science from Savitribai Phule Pune University, with a CGPA of 8.78. Completed senior and secondary school from CBSE-affiliated schools, achieving 85.2% and 78.4%, respectively.
- Projects: Led impactful projects like Lung Cancer Tumor Detection using U-Net architectures, achieving a Dice Score of 0.8. Also developed an Anomaly Detection system using CNNs, improving image classification accuracy to 82%, and enhanced Malicious Domain Detection with a 99% accuracy rate using ensemble learning.
- Technical Skills: Proficient in Python, C++, SQL, and frameworks like TensorFlow, PyTorch, and Scikit-Learn. Skilled in using data analysis tools such as Tableau, PowerBI, and MySQL, and familiar with cloud services like AWS for deployment and development.
- Certifications: Holds multiple certifications, including Deep Learning (NPTEL), Google Data Analytics, and various Dataiku certifications (Core, Advanced Designer, Developer, ML, MLOps).
- Publications: Contributed to research publications such as “Automated System For Monitoring And Maintaining Yarn Quality”, “Effects of segmentation and scaling on anomaly detection using convolutional neural networks”, and co-authored papers on enhancing malicious domain detection and air quality prediction, presented at IEEE Pune Section International Conference 2023.