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Summer Data Science Intern – London – June 2020 2245 views

Eligibility Criteria

  • Working towards a Masters or Ph.D. degree in quantitative fields like Computer Science (Artificial Intelligence, Machine Learning, Natural Language Processing, Data Mining, Data Science), Mathematics, Statistics, Operations Research, Electrical Engineering
  • Please ensure you apply with your CV in English

Application Process

  • Tech Test
  • Telephone screening
  • F2F Interview/ Mini Hackathon

Are you ready to rock machine learning, advanced analytical and statistical techniques to drive millions of choices made on their websites and marketing decisions every single day?

Their data science interns experiment with the use of advanced, emergent techniques across the business to fix the hardest problems, they take discoveries and ideas and transform them into products and actions in a dynamic, commercially driven and results-focused environment.

What You’ll Do

  • Apply solid coding skills, strong analytical and innovative thinking, Artificial Intelligence/Machine Learning expertise to quickly learn new domains and turn innovative ideas into working solutions
  • Use statistics, distributions and confidence intervals to make decisions based on data
  • Manipulate large data sets for business insights and drive solutions
  • Communicate complex analytical topics in a clean & simple way to multiple partners and senior leadership (both internal & external)

You’ll fit this role if you have

  • Working towards a Masters or Ph.D. degree in quantitative fields like Computer Science (Artificial Intelligence, Machine Learning, Natural Language Processing, Data Mining, Data Science), Mathematics, Statistics, Operations Research, Electrical Engineering
  • Solid theoretical understanding of supervised and unsupervised machine learning algorithms like Regression, Naïve Bayes, Decision Trees, Random Forests, Boosted Decision Trees, SVMs, Neural Networks, etc.

Computer Languages

  • Must-have: Scala and/or Python, SQL
  • Nice-to-have: Java, R, CUDA, C++

Data Science Technologies

  • A few of these: Spark/PySpark, MLlib, TensorFlow, Keras, PyTorch, Caffe, Python ML libs (Pandas, Matplotlib, Scipy, Sklearn, Numpy, etc)
  • Nice-to-have: Hive, Hadoop, Microsoft SQL Server

 

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