familiarity with elastic net logistic regression, random forest and XGBoost ensembles to work on supervised problems with structured, tabular data. We currently use Scikit-learn, and we're open to suggestions for additional libraries. Classification using K-means, K-Medoids or similar and the skills to evaluate solution more »
learning models and algorithms in real-world applications. - Strong proficiency in Python programming and popular machine learning libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). - Deep understanding of machine learning concepts and techniques, including supervised/unsupervised learning, deep learning, reinforcement learning, etc. - Strong communication and interpersonal more »
ML model performance using BI tools. The experience you’ll bring to the team: - Proficiency in Python, including ML/DL frameworks (e.g., Scikit-learn, TensorFlow) and visualization libraries (e.g., Matplotlib, Seaborn). - Strong SQL skills and experience with data visualization tools (e.g., Tableau). - Basic statistical analysis more »
ML model performance using BI tools. The experience you'll bring to the team: - Proficiency in Python, including ML/DL frameworks (e.g., Scikit-learn, TensorFlow) and visualization libraries (e.g., Matplotlib, Seaborn). - Strong SQL skills and experience with data visualization tools (e.g., Tableau). - Basic statistical analysis more »
and fraud detection. Requirements: Programming Proficiency: Fluency in Python with deep knowledge of statistical packages and ML/DL libraries/frameworks (e.g., Scikit-learn, NumPy, Keras/TensorFlow/PyTorch) and visualization libraries (e.g., Matplotlib, Plotly, Seaborn). Database Skills: Fluency in SQL and familiarity with data more »
proven track record of deploying models in production settings. Advanced proficiency in Python and familiarity with machine learning and deep learning frameworks (e.g. Scikit-learn, PyTorch, TensorFlow). Experience with containerization technologies (e.g., Docker, ECR) and an understanding of GPU acceleration for deep learning. Expertise in a range more »
Birmingham, England, United Kingdom Hybrid / WFH Options
Digital Waffle
used in Machine Learning and Data Science such as TensorFlow, PyTorch, and scikit-learn. Data Science and Visualisation libraries including Pandas, NumPy, scikit-learn, matplotlib, Seaborn. Cloud services used in machine learning and data science, such as Azure, OpenAI, Hugging Face, AWS ML/AI. Machine Learning more »
Strong proficiency in programming languages commonly used in machine learning, preferably Python. Experience with machine learning frameworks and libraries, such as TensorFlow, PyTorch, scikit-learn, or Apache Spark. Proven track record of developing and implementing machine learning solutions in a professional setting. Passion for exploring new technologies and more »
concepts sampling methods, Regression Properties of distributions Weighting sample-based data Statistical tests proper usage Real-world applications. Python - NumPy, SciPy, Pandas, MLlib, scikit-learn, and other common data and machine learning related libraries Working knowledge of SQL, data structures and databases (Snowflake - desirable) This is a pragmatic more »
Brighton, England, United Kingdom Hybrid / WFH Options
15gifts
based data science tech stack Python Docker & Kubernetes AWS Cloud Deep learning frameworks - Pytorch and Tensorflow HuggingFace ecosystem [optional] Other machine learning frameworks - scikit-learn, XGboost, CatBoost etc Ability to understand and develop state-of-the-art implementations Familiarity with state-of-the-art deep learning (e.g. transformers more »
knowledge of programming languages commonly used in AI development, such as Python, R, or TensorFlow. Experience with AI frameworks and libraries, such as scikit-learn, spaCy, or PyTorch. Solid understanding of data preprocessing, feature engineering, and model evaluation techniques in AI projects. Proficiency in integrating AI models with more »
in the company. Machine Learning Engineer - Ideal skillset would include: Top Academics in a relevant field Strong knowledge of TensorFlow, PyTorch, Keras and Scikit-Learn Ideally 1+ year professional experience as a Machine Learning Engineer Research minded and experimental approach to problem solving This is a very innovative more »