Associate Data Scientist

Exp – 2 – 4 Years

  • Designing and implementing Machine Learning models and algorithms.
  • Develop and maintain model deployment pipelines for many types of machine learning including supervised and unsupervised learning as well as CNNs, RNNs or other deep learning algorithms.
  • Working closely with data scientists, domain experts and sales team, both to understand model performance management requirements and design suitable inferencing instrumentation systems and practices that meet them.
  • Ensuring your model deployment, outbound data engineering and integration pipelines are architecturally and operationally integrated with inbound ingestion and contextualization pipelines designed by your peer domain architects.
  • Delivering and presenting results to team regarding their business, forecast, pipeline, and potential customers
  • Graduate or Post Graduate in computer science and data science strongly preferred, though an equivalent level engineering, data science or mathematics degree, a technical undergraduate degree and relevant experience will also be considered
  • Knowledge of traditional machine learning algorithm and techniques.
  • Experience with NLP technologies & the handling of unstructured text; Expertise in at least 1 of the following: Sentiment Analysis, Entity Extraction, Query Intent & Natural Language Understanding (NLU);
  • 2+ years of experience working with data scientists in a data engineering or production machine learning inferencing capacity, working with various types of supervised and unsupervised learning algorithms for classification, recommendation, anomaly detection, clustering and segmentation, as well as CNNs, RNNs or other deep learning algorithms
  • Knowledge of modern deep learning approaches to NLP, including but not limited to word2vec, seq2seq & FastText
  • Strong hands-on skills in SOLR/Elastic/other equivalent search engine search querying and indexing supporting web applications
  • Experience with data science toolkits like: R, Pandas, Jupyter, scikit, TensorFlow, etc.
  • Strong Python programming skills. Hands on Python experience on textual data analytics is a plus
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