Data Scientist

Summary

Developed Custom NER models based on Spacy architecture to identify the
presence of sensitive data elements and their corresponding keywords in the
documents and similar unstructured data formats
Built a classification model to identify the domain category of the document
based on the content in it. Employed data cleansing methods, significantly
enhancing data quality. Also extended support for image classification with the
help of OCR models
Implemented a layer-by-layer approach for the identification of the sensitive PII
elements in the structured data. Created and applied separate classification
models for metadata and columnar data based on the prediction result of the
former model. With this approach, the performance and accuracy were improved
considerably when compared to the primitive approach
Developed an NLP-based approach for suggesting keywords to help the user
when they are trying to add a new data element or update an existing one
Designed and built an end-to-end application for Snowflake cloud governance.
The application monitors the daily account activity and gives a summary report
of all the happenings, right from security to credit consumption, and mails the
report to the Account admin every day or based on their desired frequency
Contributed to the development of a Data migration tool from SAP Hana to
Snowflake scripts. The tool helped in the smoother and hassle-free conversion of
SQL scripts and has reduced a considerable amount of manual effort.
Worked under Agile methodology and used Azure DevOps for maintaining the
project.
Acted as a product engineer in a client PoC and was responsible for all migration
and validation for the migrated data

Expectations

A good and progressive work environment

Employment Preferences

Expected Base Salary

**0,000 INR

Academic Degree

Experience

Skills

• Python
• SQL
• Machine Learning
• NLP
• Text Classification
• Web Scrapping
• Git
• Agile
• Postman
• Flask
• HTML
• CSS
• Exploratory Data Analysis
• Predictive Modelling