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Middle NLP Data Scientist (Prom.ua) in EVO

Posted more than 30 days ago

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EVO

EVO

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Without experience
Kyiv
Middle NLP Data Scientist (Prom.ua) Kyiv, remotely Prom.ua — the largest marketplace of Ukraine, where more than 100 million products from tens of thousands of entrepreneurs from all over the country are sold. At Prom.ua: every buyer can find everything he needs at the best price: from a toothbrush to a garden cultivator and the city every entrepreneur can sell goods in the catalog of the marketplace, on the website created on the Prom platform and in the mobile application "Prom shopping".

Middle NLP Data Scientist (Prom.ua)

Kyiv, remotely

Prom.ua — the largest marketplace of Ukraine, where more than 100 million products from tens of thousands of entrepreneurs from all over the country are sold.

At Prom.ua:

  • every buyer can find everything he needs at the best price: from a toothbrush to a garden cultivator and the city
  • every entrepreneur can sell goods in the catalog of the marketplace, on the website created on the Prom platform and in the mobile application "Prom shopping".

Prom.ua in numbers:

  • 4.8 million people visit the marketplace every day
  • on more than 60,000 companies work in the marketplace
  • in the catalog of 120 million products

About the Data Science team:

We optimize various parts of the product using data and machine learning algorithms. In parallel, we are building AI systems that provide a strategic business advantage and move the company in the direction of e-commerce of the future.

Now there are 5 people in the team: 4 Data Scientists and Team Lead.

Areas of work of the team:

  • Product recommendations and personalization;
  • Search and ML-ranking;
  • Machine translation of product content;
  • Automatic moderation of goods in the catalog, classification of goods;
  • Determination of duplicate goods;
  • Generation and validation of tags for SEO

Features of working in a team:

  • high involvement in the product environment, close inter-team interaction — > little research goes under the table, many models in production
  • understanding of the set goals, focus on the result -> models do what is necessary and do not do what is not necessary
  • lack of bureaucracy , the opportunity to participate in the selection of tasks, a developed culture of initiative and responsibility for the result
  • focus on building infrastructure for greater reliability of decisions, automating routines and creating new opportunities in tasks
  • collaboration and team spirit : mutual concern and support, friendly atmosphere
  • exchange of experience: author's courses, project presentations, team grooming, etc.

We build close ties with the development and testing team. Analysts help us make a business assessment of decisions.

For day-to-day work, a raised JupyterHub server with the ability to set the necessary characteristics of the working environment can be run on a local machine if necessary. We have our own servers with video cards for training and deploying models.

Projects from the technical side:

Programming language: Python

Data analysis and processing: Jupyter Notebook, Pandas, NumPy

Machine Learning and Deep Learning: Scikit-learn, TensorFlow, PyTorch, FAISS, XGBoost

Data visualization and monitoring : Matplotlib, Seaborn, Plotly, Bokeh, Tableau, Grafana

Databases: Postgres

Big Data and distributed computing: Apache Spark, Hadoop

MLOps: MLflow, DVC, TensorFlow Serving, Python packaging, Fast API

Dags: Airflow,

Data queues: Kafka,

Search: Elasticsearch.

For this role, it is important:

  • a deep understanding of neural networks, especially NLP: understanding the differences in model architectures, application principles, hyperparameter tuning, transfer learning, learning from scratch

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  • experience in classification/segmentation/text generation using both classical methods and deep learning
  • experience in working with neural network development frameworks (PyTorch/TensorFlow)
  • experience in working with machine learning: problem formulation, data collection and research, model training, evaluation of results, analysis of model performance, preparation for deployment;
  • experience in deploying and supporting the model in production, improving existing models
  • ability to write reliable and clean code in Python, understanding and using various data structures, OOP, as well as knowledge of VC ( Git etc);
  • willingness to dive deeply into business problems and translate them into ml-terms (architecture, loss functions, metrics)

What will be a plus:

  • experience training models on data that exceeds the amount of memory, experience with high-load systems, Big Data and distributed computing
  • experience in applying MLOps practices: version control of code, data and models, automatic deployment , monitoring and logging, testing models, retraining models
  • experience with embeddings and ANN

Tasks:

  • generation of more conversion content for goods
  • improvement of the system for finding duplicate goods
  • improvement of the model of product classification and machine translation
  • research of new areas of application of machine learning to solve business problems
  • < /ul>

    Stages of selection:

    • Acquaintance with the recruiter and tech leader
    • Technical interview with project engineers
    • Final interview with the Head of Data Science Prom.ua

    We offer:

    • Official employment with the company
    • 24 calendar days of paid vacation per year, unlimited sick days.
    • Remote work. Possibility to visit the office in Kyiv
    • Medical insurance
    • Services of a corporate psychologist

Without experience
Kyiv
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