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.
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