TensorFlow, and PyTorch Practical experience with Generative AI and exposure to leading LLM platforms (Anthropic, Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Strong skills in data preprocessing, wrangling, and augmentation techniques Experience deploying scalable AI solutions More ❯
emerging trends and technologies in the field of data science. Requirements Proven experience as a data scientist using Python and a range of libraries (Numpy, Pandas, Scikit-Learn, Matplotlib, Plotly etc.). Strong expertise in statistical modelling, machine learning, and data mining techniques. Experience in computer vision is essential. Data engineering (pipelines, databases, infrastructure), ideally with AWS experience would be More ❯
Development Lifecycle. What you'll bring to the role and MHR Advanced Python experience e.g. Poetry, FastAPI, LlamaIndex, OpenAI, Pydantic, Dependency Injector, Jupyter Notebooks, Pandas, NumPy, Scikit-learn, SciPy, Plotly Experience with Azure AI Studio Vector Database, e.g. Qdrant,ChromaDB Databricks LLMs Prompt Engineering for LLMs Experience of testing and deployment of data science models to production. Learning and application More ❯
