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Data Scientist

Bangalore Data Science
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  • About DRAUP

    Draup is an enterprise decision-making platform for global CXO leaders in sales and talent domains. Draup combines machine learning with human curation to help organizations make data-driven strategic decisions. The platform is powered by machine-generated models, which are augmented by a team of analysts adding their learning-based insights to provide a 360-degree transactable view of their sales and talent ecosystem.

  • Job Description

    The Data Scientist at Draup will be responsible for analysing huge volume of unstructured text data and deriving insights from the same. You will be working heavily on NLP techniques such as POS Tagging, NER, Pattern Recognition, Text Clustering and Classification. You will also be responsible for creating end-to-end ML pipelines for deployment of models.

  • What you will need

    • At least 3 years industry experience in one or more full-time Data Science/ML role.
    • Excellent proficiency in Python.
    • Hands-on knowledge of using Python libraries like Pandas, NumPy, SciPy, Scikit-Learn, NLTK, SpaCy etc.
    • At least 2 years of experience working with textual data.
    • In depth understanding of distributed text representation algorithms like Word2Vec, GLOVE, Doc2Vec etc.
    • Knowledge of different classification and clustering techniques.
    • Good understanding of Deep Learning algorithms.
    • Hands-on knowledge of TensorFlow/Keras framework.
  • What will give you an advantage

    • Experience in Spark or other distributed computing frameworks.
    • Understanding of AWS Sagemaker.
    • Experience working in a start-up environment.
  • Who you are

    • Bachelor/Master degree in Engineering preferably from a top tier engineering college like IIT/NIT/BITS etc.
    • Experience of 2.5 – 5 Years working in a Machine Learning role.
Found fit? Apply now!
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Each one at Draup is unified by the sole vision of building an amazing data product. We are proud to declare that Draup is an embodiment of equal opportunity principles. We do not unlawfully discriminate on the basis of gender identity or expression, race, ethnicity, religion, national origin, age, sex, marital status, physical or mental disability, veteran status, sexual orientation, and any other category protected by law.

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