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sharatsachin/README.md

Sharat Sachin

"Making machines predict the future"

πŸ‘¨β€πŸ’» About Me

I am an engineer currently working in the data science team at Nagarro, Gurgaon. I got my undergraduate computer science degree from the Bharati Vidyapeeth College of Engineering, Delhi, and master's degree from BITS Pilani. I am skilled in various fields and frameworks including:
  • βœ… Data Visualization/Analytics: Matplotlib, Seaborn, Plotly
  • βœ… Data Science: PyTorch, TensorFlow, Scikit-learn, Hugging Face, OpenCV, NumPy, Pandas, NLTK, Dask
  • βœ… Algorithms, Data Structures: Dynamic Programming, Graph Theory, Trees, Arrays
  • βœ… Web Scraping: BeautifulSoup, Scrapy
  • βœ… Maths and Statistics: Statsmodels, SciPy
  • βœ… Domains: Regression, Classification, NLP, Computer Vision, Time Series
  • βœ… Data Engineering: SQL, PySpark, dbt
  • βœ… MLOps: MLflow
  • βœ… APIs: Flask, FastAPI
  • βœ… Cloud Platforms: GCP, AWS
  • βœ… Industry skills: Linux, Git, Docker, LaTeX, Markdown

πŸ‘¨β€πŸ’Ό Experience

Nagarro - Senior Engineer (Data Scientist)

October 2020–Present

  • 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.

πŸŽ“ Academics

Institution Degree Year CGPA/Percentage
BITS Pilani (Work Integrated) M.Tech, Data Science and Engineering 2022- Ongoing
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%

🧰 Tech Stack

GCP

Cloud Storage BigQuery Cloud Run VM Vertex AI Dataproc Earth Engine Container Registry

AWS

S3 EC2 ECR Kinesis Lambda RDS SageMaker

πŸš€ Personal Projects

  • YouTube Playlist length - A web-app to find the length of playlists on Youtube, with over 10k weekly visitors, and 600+ GitHub stars.
  • IPU Results website - A website to check the results of the semester exams of IP university.

πŸ“œ Certifications

πŸ† Achievements

  • 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

Pinned Loading

  1. ytplaylist-len ytplaylist-len Public

    A small web app to get the lengths of playlists on YouTube

    Python 736 113

  2. ipresultss-website ipresultss-website Public

    Website for display of IPU results for CSE batch of 2016.

    Jupyter Notebook 3 1

  3. sharatsachin.github.io sharatsachin.github.io Public

    CSS 3