Work with cross-functional teams to identify business challenges and define data-driven solutions.
Design, build, and deploy end-to-end machine learning pipelines for both structured and unstructured data, encompassing data preprocessing, feature engineering, model training, and exploratory data analysis (EDA).
Conduct model evaluation, tuning, and performance monitoring, to ensure robustness, scalability, and seamless integration with engineering teams for product and service deployment.
Mentor junior data scientists, and contribute to building best practices in data science and AI.
Write optimized SQL queries to extract and manipulate large-scale datasets from relational databases.
Requirements:
Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Statistics, or related field with 2-5 years of hands-on experience
Fluent in English both in oral or written is a must
Strong expertise in Python (NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch).
Proficiency in SQL and relational database management.
Experience with computer vision frameworks (OpenCV, YOLO, Detectron, etc.)
Solid understanding of machine learning algorithms (supervised, unsupervised, deep learning).
Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or BI tools).
Familiarity with cloud platforms (AWS, GCP, or Azure) and MLOps practices is a plus.
