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Data Scientist Intern

World Wide Technology

Updated on: 16 August 2024

Additional Details

Website

www.wwt.com

website

Work Location

Gurgaon, India

location

Job Type

Internship + Fte

job_type

Batch

2025 | 2024 | 2023

batch

Stream Required

BE/B-TECH

stream

Salary

15 - 18 LPA (Expected)

salary

Job Description

Role Responsibilities/Accountabilities:  

  • Work closely with WWT business, engineering and technology teams  
  • Extract data from customer source systems or databases into software or development environments  
  • Perform EDA and data processing to analyze data using programming tools such as Python
  • Use statistical and programming tools such as Python to analyze data and develop solutions to business problems  
  • Perform quality control of deliverables  
  • Prepare reports and presentations and present findings  
  • Stay current with new development in Big Data and AI / Deep Learning (e.g. Spark, AWS, Azure ML, Pytorch)  and Generative AI (Langchain etc.)
  • Provide thought leadership in algorithmic and process innovations and creativity in solving unconventional problems
  • Interact with clients including in-person meetings, towards making business recommendations with effective presentations of findings, including visual displays of quantitative information.
  • Research and develop internal capabilities to enhance the skill sets on latest data science developments, work towards producing innovative solutions to the existing challenges.
     

___________________________________________

Qualifications 

Required:  

  • Basics of supervised (linear and logistic regression, time series forecasting) & unsupervised learning algorithms (K-Means, K-NN etc.) 
  • Basics of Statistics and hypothesis testing 
  • Programming experience in either Python, R or Java 
  • Basics of Database and experience in SQL  
  • Proficient in functional & object-oriented programming (OOPS) concepts 
  • Experience with MS tools (e.g.: Excel, PowerPoint)  
  • Good communication skills 

Preferred: 

  • Experience of working with Big-Data platforms (e.g.: Hadoop, Apache Spark, Hive, Hbase, etc.) 
  • Academic or project experience with Deep Learning toolkits (e.g.: TensorFlow, Keras, Theano, PyTorch, Caffe, etc.)  
  • Worked on UNIX based systems and experienced in command line utilities (sed, awk, Makefile, etc.) 
  • Experience of working with NoSQL databases

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