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Sreekanth

Data scientist
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Location Hyderabad
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Member since30+ Days ago
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Candidate Information
  • User Experience
    Experience 7 Year
  • Cost
    Hourly Rate$30
  • availability
    AvailabilityImmediate
  • work from
    Work FromOffsite
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    CategoryInformation Technology & Services
  • back in time
    Last Active OnJuly 18, 2024
Key Skills
Data ScientistMachine LearningPythonPysparkMicrosoft AzureADF
Summary

PROFESSIONAL EXPERIENCE


Amnet Digital Jan 2020 – Present

Role: Senior Data Scientist


Customer Mosaic:

● A smart AI application to bring the customer360 degree view on one platform. 

● Involved in design and development of Data Architecture.

● Design and developed the model to the top 5 similar companies using K-Mode clustering.

● Developed the Fuzzy logic to integrate with Third party data.

Propensity:

● Developed Propensity to buy models to classify potential customers by their likelihood to purchase a particular product.

Demand Forecasting:

● Developed and monitoring the Demand Forecasting models with ARIMAX by analyzing the historical data to estimate and predict customers' future demand for a product or service.

ePro:

● Developed a model to classify the customers who have the likelihood to use procurement services. Used Dataiku to develop and deploy.

Image extraction from PDF:

● Developed an application to extract cartoons from old scanned newspapers which are scanned PDF files using OpenCV and CNN. 

Sensitive text extraction from PDF:

● Developed an application to extract sensitive information from text using openCV and deep learning techniques.

SportsAnalytics:

● Developed a SportsAnalytics application to identify the perfection in cover drive shot using deep learning. 

Smart Routing masking sensitive data:

● Extracting and masking the sensitive data like customer name, phone number and address etc from text data which is generated from sales team chatbot.

● Developed a smart application which will mask all the sensitive data.


Renewal Win rates:

● Developed a predictive model to classify the list of customers who will buy again or extend the validity of products that they have already purchased.


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