leading and delivering successful data science projects. Proficiency in programming languages such as Python, R, or Scala. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong knowledge of statistical modelling, data mining, and data visualization techniques. Experience with big data technologies (e.g., Hadoop, Spark) and more »
discipline eg. Statistics, Mathematics, Physics, Machine Learning Deep expertise in Python (production-level) and SQL Proficiency in machine learning libraries (eg. Pandas, scikit-learn, TensorFlow) and experience with MLOps frameworks for model deployment Exceptional communication skills, able to engage confidently with non-technical stakeholders Experience resolving operational or customer more »
and a good understanding of data engineering & MLOps. Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch. Passion for learning new skills and staying up-to-date with ML algorithms. Knowledge of fundamental machine learning concepts (feature engineering, algorithms more »
with a strong focus on machine learning and time series forecasting. Expertise in Python and its data science libraries (e.g., Pandas, NumPy, Scikit-Learn, TensorFlow, PyTorch). Solid understanding of ML and data pipeline architectures and best practices. Experience with big data technologies and distributed computing (e.g., Spark, Hadoop more »
data manipulation Prior work experience with analytical/statistical data analysis tools such as R and Python and deep learning libraries such as PyTorch, TensorFlow, Keras Familiarity with data visualization and dimensionality reduction algorithms Ability to develop, benchmark and apply predictive algorithms to generate hypotheses Comfortable working in cloud more »
Medoids or similar and the skills to evaluate solution suitability e.g., Silhouette Score. Confident in the skills needed to deploy deep learning, ideally through Tensorflow, including transformer architectures. Natural language processing capabilities, including skills in sentiment analysis and using and localising large language models (transformers), ideally through the Hugging more »
of the associated long-term risks and ethical considerations. Technologies: AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
of the associated long-term risks and ethical considerations. Technologies: AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
of the associated long-term risks and ethical considerations. Technologies: AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
of the associated long-term risks and ethical considerations. Technologies: AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
of the associated long-term risks and ethical considerations. Technologies: AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
understanding of the associated long-term risks and ethical considerations. AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
understanding of the associated long-term risks and ethical considerations. AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
understanding of the associated long-term risks and ethical considerations. AI/ML Frameworks and Tools: Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
legal field, balanced with a deep understanding of the associated long-term risks and ethical considerations. Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
legal field, balanced with a deep understanding of the associated long-term risks and ethical considerations. Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
or a related field. Strong background in deep learning, with hands-on experience in developing and implementing deep neural networks using frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in programming languages such as Python and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn). more »
London, England, United Kingdom Hybrid / WFH Options
High Frequency Trading Firm
or a related field. Strong background in deep learning, with hands-on experience in developing and implementing deep neural networks using frameworks such as TensorFlow, PyTorch, or Keras. Proficiency in programming languages such as Python and experience with data manipulation and analysis libraries (e.g., pandas, NumPy, scikit-learn). more »
and deploying machine 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 more »
statistical analysis, and data engineering. Proficiency in programming languages such as Python, R, and SQL, and experience with data science tools and frameworks like TensorFlow, PyTorch, and Spark. Demonstrated ability to lead and inspire a team of data professionals, fostering a collaborative and high-performing work environment. Excellent problem more »
statistical analysis, and data engineering. Proficiency in programming languages such as Python, R, and SQL, and experience with data science tools and frameworks like TensorFlow, PyTorch, and Spark. Demonstrated ability to lead and inspire a team of data professionals, fostering a collaborative and high-performing work environment. Excellent problem more »
and advanced analytics technologies, coupled with the ability to discern their feasibility and long-term impact. Expertise in popular machine learning libraries such as TensorFlow, PyTorch, and Keras. Proficient in using AI/ML platforms like Google AI Platform, AWS SageMaker, or Azure Machine Learning for model development and more »
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 of machine learning more »
the insurance domain , with hands-on experience across predictive modeling, natural language processing, computer vision, and reinforcement learning. Proficiency in machine learning frameworks (e.g., TensorFlow, PyTorch), programming languages (e.g., Python, Java), and cloud platforms (e.g., AWS, Azure, GCP). Thorough comprehension of insurance business processes and regulatory frameworks, with more »
Boultham, Lincolnshire, United Kingdom Hybrid / WFH Options
Pro Box Recruitment
development methodology Familiarity with CI/CD and pipeline automation Familiarity of machine learning principals/pipelines and associated toolsets such as Pytorch and Tensorflow Familiarity with Azure, AWS, GCP products and services - Knowledge of technologies including: Docker or Kubernetes Distributed version control systems such as Git Exposure to more »
Employment Type: Permanent
Salary: £50000 - £70000/annum Salary dependent on experience
