RESPONSIBILITIES
- Manage end-to-end data annotation workflows on the annotation platform.
- Configure and optimize data storage solutions to support annotation processes.
- Develop dashboards to visualize database statistics and insights.
- Design and implement data storage systems for medical datasets, including schema development and updates.
- Build and maintain automated data flows and pipelines for efficient data processing.
- Perform medical data analysis, data exports, queries, and validations to support the ML team.
REQUIREMENTS
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Bachelor or Master degree in Computer Science or related field.
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1+ years of relevant experience in data engineering.
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Strong Python skills with experience in data-focused libraries (Pandas, NumPy, etc.).
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Experience with SQL for querying and data manipulation.
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Proven experience with image datasets cleaning and pre-processing for ML needs.
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Experience with cloud storage solutions such as Google Cloud and AWS.
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Experience in designing and managing scalable data storage solutions, including relational databases, e.g. PostgreSQL.
STRENGTHS THAT BENEFIT US
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Experience with annotation platforms, specifically those designed for medical data labeling.
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Industrial experience in building and maintaining ETL pipelines for processing large datasets, including imaging data.
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Working with DICOM
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Experience with relational databases (PostgreSQL)
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Experience with Grafana in terms of dashboards creation
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Experience with Docker and k8s
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Experience with cloud deployment (AWS, GCloud).
WE OFFER:
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Company stock options.
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Fast career growth
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Positive team culture
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Being part of the decision-making process and impacting our product’s development.
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Participation in conferences and publications.
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Diverse and thrilling projects with American and European scientists and doctors
Ключевые навыки
- Python
- PostgreSQL
- SQL
- pandas
- Numpy
- Jupyter Notebook
- Matplotlib
- NoSQL
- Data Mining
- Big Data
- Английский — C1 — Продвинутый
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Вакансия опубликована 30 января 2025 в Москве