Responsibilities
- Collaborate proactively with the data science team to implement new features that address evolving data needs.
- Design, build, and maintain data science and machine learning pipelines, including data retrieval, preprocessing, feature engineering, model training, and inference.
- Analyze and visualize results to extract meaningful insights from complex datasets.
- Share technical knowledge and project insights with other teams to support cross-functional collaboration.
- Participate in selecting appropriate tools, technologies, and strategies for different data science scenarios.
- Contribute to continuous improvement of data workflows and support integration with ML operations processes.
Qualifications
- Bachelor’s degree in Information Technology, Computer Science, or a related field.
- More than 2 years of hands-on experience as a Data Scientist.
- Strong foundation in mathematics, statistics, and tensor calculus.
- Solid experience with Python, including libraries such as Scikit-learn, NumPy, Pandas, and Matplotlib.
- Proficiency in machine learning and deep learning techniques, including practical experience with NLP and computer vision models such as BERT and ResNet.
- Experience with gradient boosting algorithms (e.g., XGBoost or LightGBM).
- Skilled in at least one neural network framework (TensorFlow/Keras or PyTorch), with a good understanding of neural network architectures.
- Experience building end-to-end machine learning pipelines, including data preprocessing, training, inference, and deployment.
- Familiarity with databases such as PostgreSQL, MongoDB, and SQL.
- Working knowledge of GitHub/GitLab CI/CD and container platforms like Docker or Kubernetes.
- experience with AWS or Azure, and working knowledge of Spark or Airflow is a plus.
- Upper-intermediate English proficiency or higher.
Required Skills
- Python
- SQL
- MongoDB
- Postgres
Job Details
- Location Europe - Europe
- Industry Information & Communication Technologies
- Job Type Full-Time
- Degree Bachelor
- Experience 2+
- Nationality Unspecified
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