- ✅ Data Visualization/Analytics: Matplotlib, Seaborn, Plotly
- ✅ Data Science: PyTorch, Scikit-learn, Hugging Face, OpenCV, NumPy, Pandas, NLTK, Dask
- ✅ Algorithms, Data Structures: Dynamic Programming, Graph Theory, Trees, Arrays
- ✅ Web Scraping: BeautifulSoup
- ✅ Maths and Statistics: Statsmodels, SciPy
- ✅ Domains: Regression, Classification, NLP, Computer Vision, Time Series
- ✅ Data Engineering: SQL, PySpark, dbt
- ✅ MLOps: MLflow
- ✅ APIs: Flask, FastAPI
- ✅ Cloud Platforms: GCP, AWS
- ✅ Industry skills: Linux, Git, Docker, LaTeX, Markdown
- Inventory Management Using Reinforcement Learning: Developed a system utilizing reinforcement learning (RL) algorithms, such as Q-learning or Deep Q-learning, to optimize inventory levels. Implemented algorithms to learn optimal stocking levels based on demand patterns and cost considerations, resulting in significant cost savings for the business.
- Product Return Forecasting: Utilized statistical modeling techniques, such as time series analysis or machine learning, to analyze historical data and identify patterns related to product returns. Developed models to predict future return rates, enabling the business to better manage inventory and plan resources efficiently.
- Multi Touch Attribution Using Markov and Shapely: Developed a model to attribute sales to different marketing channels using Markov chains and Shapely values. The model helped the business understand the impact of each marketing channel on sales and optimize marketing strategies accordingly.
- Budget Reallocation Using Linear Programming: Worked on optimizing budget allocation across various campaigns and ad groups using linear programming techniques. Analyzed campaign performance data and market trends to determine the most effective allocation strategy, resulting in improved performance and resource utilization.
- Scheduling Accelerator Using Ant Colony Optimization: Designed and implemented an internal demo to optimize the workflow of a manufacturing process. Utilized Ant Colony Optimization (ACO) algorithm to schedule various jobs on different machines, improving production efficiency and reducing idle time.
- Demand forecasting for a leading cosmetics company - Delivered an end-to-end demand forecasting solution accurately predicting demand for thousands of products across multiple online marketplaces. Utilized gradient boosting models and time-series models like Prophet / Sarimax to build a weighted forecast at product level.
| Institution | Degree | Year | CGPA/Percentage |
|---|---|---|---|
| BITS Pilani (Work Integrated) | M.Tech, Data Science and Engineering | 2022-2024 | 9.07 CGPA |
| Bharati Vidyapeeth College of Engineering New Delhi | B.Tech, Computer Science and Engineering | 2016–2020 | 8.61 CGPA |
| Sahoday Sr. Sec. School New Delhi | Class 12th | -2016 | 92.4% |
| Cloud Storage | BigQuery | Cloud Run | VM | Vertex AI | Container Registry |
|---|
| S3 | EC2 | ECR | Kinesis | Lambda | RDS | SageMaker |
|---|
- YouTube Playlist length - A web-app to find the length of playlists on Youtube, with over 10k weekly visitors, and 700+ GitHub stars.
- IPU Results website - A website to check the results of the semester exams of IP university.
- AWS Certified Machine Learning – Specialty Offered by AWS, October 2022
- AWS Certified Cloud Practitioner Offered by AWS, January 2022
- Deep Learning Specialization Offered by deeplearning.ai on Coursera, August 2020
- Machine Learning Offered by Stanford University on Coursera, Feb 2020
- Plotting, Charting & Data Representation in Python Offered by University of Michigan on Coursera, April 2018
- Introduction to Data Science in Python Offered by University of Michigan on Coursera, April 2018
- Rank 1 in HackerBlocks CodSule, October and November 2018
- Selected for onsite regional at ICPC Amritapuri 2019
- Won The Rookie award at Nagarro in my first year
- Finished all problems in Advent of Code 2021, finishing in first place at Nagarro