Data Scientist2020 - 2021AAYS Analytics
Technologies: Python 3, Azure, PySpark, Statistical Methods, Machine Learning, Agile Sprints, Agile, Python, Deep Learning, DeepAR, Demand Planning, Git, Agile Data Science, Data Science, Time Series, Time Series Analysis, Time Series Forecasting
- Extracted, aggregated, and analyzed large data sets to provide actionable insights; also created intuitive visualizations to convey those results to a broader audience.
- Analyzed profit erosion for a finance client and discovered adverse cost components which helped optimize existing revenue streams.
- Developed and deployed an intelligent supply chain solution for a fast-fashion client that helped the client maintain optimal stock levels for favorable clothing styles and increased earnings.
- Contributed to building the data infrastructure for client organizations on Azure, including setting up a data lake, ETL (data engineering) pipelines, and machine learning pipelines.
- Acted as a data scientist to build and operationalize reliable and scalable machine learning pipelines for data preparation, model training, and prediction at scale. Deployed data pipelines on the Azure cloud platform.
- Led client meetings and presented compelling findings and a story for the "why" of these findings to a wide range of stakeholders with insightful visualizations using Power BI reports.
Data Scientist2018 - 2020Aptus Data Labs
Technologies: Python 3, Machine Learning, Deep Learning, Agile, CI/CD Pipelines, Docker, Kubernetes, AWS, Data Science, Agile Data Science, Time Series, Time Series Analysis, Time Series Forecasting
- Served as a data scientist to partner with clients to understand their business pain points and design analytical solutions to address those; also helped clients use their organization's data to drive strategic business decisions.
- Focused on data preprocessing, machine learning modeling, and the operationalization of ML models.
- Developed and deployed an LSTM-based (named entity recognition) model for a pharma client that helped reduce manual efforts by 90%.
- Developed and deployed an inventory optimization platform that used hybrid time series models for long-term forecasting and demand sensing. This helped the client maintain optimal inventory for products and plan demand fulfillment.
- Developed and deployed a deep learning pipeline for a manufacturing client that performs text localization and recognition, helping reduce human error and operations costs by 40%.
Data Science Intern2018 - 2018Aptus Data Labs
Technologies: Python 3, Python, Data Science, Agile Data Science, AWS, Amazon Web Services (AWS), Docker, Kubernetes, Time Series Analysis, Time Series, Time Series Forecasting
- Worked as a data science intern on time series analysis and text analytics projects.
- Implemented, for a Fortune Global 500 oil-and-gas company, a proof of concept for a supply chain optimization project by creating a time series model to forecast the load(oil, gas) requirement at different ports based on historical data.
- Developed, for a multinational pharmaceutical company, text-analyzing software to migrate thousands of documents into a different format. It helped them reduce the operational cost of merger by 5%.
- Created tools for a sanity-check-like document comparison tool to visually analyze the difference in two almost similar documents. Successfully automated the whole process and reduced manual effort to a staggering 1-2% of the initial effort.
Machine Learning Intern2017 - 2017Tata Consultancy Services
Technologies: Machine Learning, Python 3, Python, Deep Learning, OCR, Text Recognition, Text Detection, Computer Vision
- Worked on a project called "Image Attribute Extraction" which includes extraction of text from product images and populating specific attributes with extracted text.
- Developed a Keras model for text recognition using connectionist temporal classification loss.
- Developed a CNN-RNN based neural network to detect text in product images that helped the team build a more robust text extraction.