Harmonya-Senior Data Scientist

  • Harmonya
  • Tel Aviv, Israel
  • Full-time
About The Position

Harmonya helps retailers and manufacturers overcome the limitations caused by legacy data structures and unlock the true value of their data. 

Harmonya is an AI-powered product data classification and enrichment platform for retailers and manufacturers. Leveraging proprietary ML and AI models, Harmonya synthesizes data from trillions of alternative data points to generate a holistic and dynamic view of products sold across the country.


In this role, you will: 

  • Be part of a data science team where you will lead end-to-end ML projects from data extraction through model validation to model deployment.
  • Develop various ML Models, mostly focused on NLP models such as named entity recognition, keyword extraction, and text classification to create the ultimate taxonomy in the world of fast-moving products, Graph theory model to identify various relationships between products, and trend analysis models to surface the most interesting consumer-related trends
  • Discover and translate business challenges into data pipelines and models.
  • Manage and design customer-specific analytical solutions using Machine Learning.
  • Work closely with management, and data engineering teams to integrate data collection, data quality, and core model output into production systems.
  • Convey complex analysis results clearly and with conviction to stakeholders at all levels.
  • 5+ years of experience with data science projects from conception to production.
  • Experience with NLP practices such as part of speech tagging, named entities recognition, and word embeddings. 
  • Broad knowledge of multidisciplinary data science modeling techniques and their use within the industry.
  • Fluency in Python and hands-on experience with data science and NLP packages (spaCy, nltk, gensim, TensorFlow, PyTorch, scikit-learn).
  • Experience in large-scale training and model evaluation in an enterprise environment.
  • Big Advantage: Experience with Cloud Machine Learning Platforms (Google ML Engine, AWS SageMaker) and/or commercial tools (DataRobot, BigML, or others).

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