Middle Data Scientist (Prom.ua) in EVO

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

At Prom.ua:

• every buyer can find everything they need at the best price: from a toothbrush to a cultivator for the garden and garden.
• every entrepreneur can sell goods in the marketplace catalog, on to the website created on the Prom platform and the "Prom Shopping" mobile application.

Prom. ua in numbers:

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

About the Data Science team:

We optimize different 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.

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

Directions of the team's work:

• Product recommendations and personalization
• Search and ML ranking
• Machine translation of product content
• Automatic moderation of products in the catalog, product classification
• Definition of product duplicates
• Generation and validation of tags for SEO

Features of working in a team:

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• Great involvement in the product environment, close inter-team interaction — > little research goes under the table, many models in production
• Understanding the set goals, focus on the result -> models do what necessary, and do not do what is not necessary
• Absence of bureaucracy, the opportunity to participate in the selection of tasks, a developed culture of initiative and responsibility for the result
• Focus on infrastructure development for greater reliability of decisions, automation of routine and creation of new opportunities in tasks
• Collaboration and team spirit: mutual care and support, friendly atmosphere
• Exchange of experience: author's courses, project presentations, team grooming, etc.

We build close ties with the development 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.

Technology stack:

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.

Important for this role:

• deep understanding of neural networks, especially in NLP
• experience working with frameworks for developing neural networks (pytorch/tf)
• experience 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 a model in production, improving existing models
• ability to write reliable and clean code in Python, understanding and using various data structures, OOP, and also having VC (Git etc);
• experience working with databases, SQL queries
• willingness to dive deeply into business tasks and translate them into ml-terms (architecture, loss functions, metrics)

What will be a plus:

• experience in writing neural networks from scratch according to the description from articles and studies
< li>experience in training models on data exceeding the amount of memory, experience with highly loaded 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 working with embeddings

Tasks:

• improving the system for finding duplicate products
• improvement of product classification model and machine translation
• development of new recommender system models
• generation of more conversion content for products
• exploration of new areas of application of machine learning for solving business problems

Stages of selection:

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

We offer:

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