Madhusudan C.

Madhusudan C.

"Data is gold! I know the science of making amazing ornaments out of it" | Data Science | Python

Bengaluru , India

Experience: 2 Years


Bengaluru , India

"Data is gold! I know the science of making amazing ornaments out of it" | Data Science | Python

16457.1 USD / Year

  • Immediate: Available

2 Years

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About Me

Machine learning enthusiast | Data Science | Advanced Analytics | Python | NLP
Possess knowledge of machine learning models for classification, regression, clustering etc. 
Have experience in cleaning, pre-processing and modelling of data...

Currently working as a big data developer and also doing some machine learning projects alongside.
I write at:

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Portfolio Projects






• GIS Data Load Utility: I developed a utility that loads/transform large Geojson files that contains geospatial data into Hive tables • Data transformation: Under this thread I developed mappings to transform data as per data scientists’ requirements and load the data into Exadata database. • Kafka Development: I developed Kafka pipelines to load data from source to HDFS in AVRO format. • NIFI Development: I developed NIFI pipelines to extract data from SFTP and process it to write into Kafka topics. • Code deployment management: I took the ownership to deploy different code bases to multiple environments. • Data Loads: I loaded the history data in Integration environment using various pipelines that used utilities, Oracle Golden Gate, Kafka, ODI etc. • Defect Fix: Under this thread I worked on resolving various data defects from loads and data scientists’ perspective. • Data Load Approach Design: I was involved in designing the approach for loading the historical data in production. • Scripting: Created various shell scripts to automate things such as searching files in various environment, reading various logs etc. • Python Automation: Developed utilities to automate lot of redundant development tasks.

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Preferred Language

  • English - Fluent

Available Timezones

  • Mountain Daylight [UTC -6]

  • Dubai [UTC +4]

  • New Delhi [UTC +5]

  • China (West) [UTC +6]

  • Singapore [UTC +7]

  • Hong Kong (East China) [UTC +8]