large and complex data sets to extract insights and identify trends Advanced programming skills with Python, including experience with Jupyter notebooks, PyTest, Pandas, SciKit, PyTorch, type-checking, functional programming, CI/CD, and Git A borad background in machine learning for customer and marketing purposes around pricing, promotions, recommendations, Computer more »
deployment, monitoring and maintenance of models in production desired Expertise in using and implementing cutting-edge machine learning algorithms, frameworks, and libraries, such as PyTorch, Keras, Tensorflow to solve clustering, classification, regression, and optimization problems on large scale data sets Hands-on experience with modern NLP methods required. Specifically: Transformers more »
data science, e.g., SQL, R and Python alongside the ability to use tools and packages such as Alteryx, Jupyter notebook, R Markdown, TensorFlow, Keras, Pytorch, Apache Spark etc. oPractical proficiency in producing reproducible code and pipelines including documentation, governance and assurance frameworks, automation and code review using tools such as more »
problems and solid knowledge of mathematical foundations of ML algorithms. Proficiency in Deep Learning Architectures (e.g., MLP, RNN, CNN) and popular frameworks (e.g., TensorFlow, PyTorch, Keras). Expertise in multiple open-source machine learning libraries (e.g., scikit-learn, Pandas, NumPy, Matplotlib, seaborn, Spacy, NLTK, transformers, Hugging Face, pymupdf). Practical more »
in natural language processing (NLP) and its applications. Solid coding level in Python programming language, with experience in leveraging available libraries, like Tensorflow, Keras, Pytorch, Scikit-learn, or others, to dedicated projects. Previous experience in working on Spark, Hive, and SQL, Preferred qualifications, capabilities, and skills Financial service background PhD more »
Engineer or similar role, with a strong emphasis on engineering Proficiency in Python programming and experience with relevant libraries/frameworks such as TensorFlow, PyTorch, scikit-learn, etc. Extensive experience of deploying a cloud platform (GCP, AWS or Azure) Strong proficiency in NumPy for numerical computing and data manipulation tasks. more »
developing and deploying machine learning solutions in production environments. Proficiency in Python programming and experience with machine learning libraries and frameworks such as TensorFlow, PyTorch, or scikit-learn. Experience with chatbot development frameworks and platforms (e.g., Dialogflow, Rasa) and knowledge of natural language processing (NLP) techniques and tools. Familiarity with more »
in production at scale. Deep knowledge of machine learning algorithms applied to solving business problems. Proficiency in Python and popular Data Science frameworks (e.g. pytorch, pandas, numpy etc) and MLOps platforms (e.g. Sagemaker) Solid understanding of metrics, benchmarking and evaluation methodology AI-powered user-facing products. Experience working in highly more »
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 the ability more »
in programme) Python Programming Language – 4-5+ years of experience in a Data Science setting Experience in AI/Machine Learning + either PyTorch/TensorFlow Experience with NumPy/Pandas Matplotlib SQL/MySQL/database experience Please note, this is a hybrid position. Candidates who cannot travel more »
methodologies and algorithms Expertise in popular data science platforms such as Alteryx and Python, including libraries and frameworks like NumPy, SciPy, Pandas, NLTK, TensorFlow, PyTorch, and Airflow Strong understanding of statistical analysis, encompassing distributions, statistical testing, regression, and other techniques Experience handling unstructured data sets Familiarity with software engineering principles more »
Greater London, England, United Kingdom Hybrid / WFH Options
Renude
learning with one or more of the following: generative models, segmentation, object detection, classification, model optimisations Experience working with machine learning frameworks such as PyTorch, TensorFlow or Keras Experienced with foundational Large Language Models (LLMs) APIs Experience in LLMs quantitative analysis Exposure to MLOps practices Familiarity with version control systems more »
the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to work effectively more »
a partnership model, conveying information clearly and creates a sense of trust with stakeholders. Preferred qualifications, capabilities and skills Experience with deep learning frameworks (pytorch, tensorflow) Experience with big-data technologies (Spark, Hadoop) or distributed computation frameworks (Dask, Modin) Hands on experience with Natural Language Processing (NLP) and Large Language more »
within the insurance domain , Hands-on experience across predictive modelling, natural language processing, computer vision, and reinforcement learning. Proficiency in ML 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 the ability more »
using techniques such as machine learning, deep learning, natural language processing, computer vision, etc. Knowledge of multiple AI frameworks and platforms, such as TensorFlow, PyTorch, Keras, Azure AI, AWS Sagemaker and Bedrock, etc. Experience of designing and deploying Generative-AI based solutions Knowledge of AI architectures, patterns, and best practices more »
in a tech team using a diverse tech stack including: Backend: Python, FastAPI, PostgreSQL, Vespa, SQLAlchemy, Flask. Frontend: React, Next.js. Data Science: Python, Jupyter, PyTorch, Pandas, Spacy, Huggingface, Numpy, Streamlit, Weights and biases. Infra: Pulumi, Docker, AWS AppRunner, Step Functions, Grafana cloud monitoring, Prefect. Who you are Must haves: Experience more »
on machine learning or similar. Experience of developing and deploying state-of-the-art recommendation algorithms using Python and relevant libraries (e.g., TensorFlow/PyTorch/Keras/etc) in the Python ecosystem. Have strong experience in DevOps combined with AWS and technologies such as Docker, Kubernetes, EC2, ECR, ECS more »
and optimising marketing spend Programming proficiency in Python, SQL, Bash, and Excel, including experience with Jupyter notebooks, type-checking, functional programming, PyTest, Pandas, SciKit, PyTorch, CI/CD, and Git Experience with Docker, Kubernetes, and cloud platforms such as AWS, Databricks, Snowflake Experience visualizing data using Plotly and Matplotlib In more »
analysis/Engineering Solid understanding of financial markets, investment products, and risk management concepts. Experience with quantitative modeling libraries and frameworks (e.g., QuantLib, TensorFlow, PyTorch). Knowledge of risk metrics and methodologies (e.g., VaR, CVaR, stress testing, scenario analysis). If this sounds like you, please do get in touch more »
A minimum of 4 years' experience in Python, with a strong foundation in machine learning principles. Proficient in modern AI frameworks and libraries, notably PyTorch and Hugging Face. Experienced with foundational Large Language Models (LLMs) APIs in production environments. Skilled in deploying machine learning solutions to production. Strong communication skills more »
a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database, and Cosmos DB. Understanding of CI/CD pipelines, containerization more »
Machine Learning Engineer or similar. Experience of developing and deploying state-of-the-art recommendation algorithms using Python and relevant libraries (e.g., TensorFlow/PyTorch/Keras/etc) in the Python ecosystem. Have strong experience in DevOps combined with AWS and technologies such as Docker, Kubernetes, EC2, ECR, ECS more »
and deployment Understanding of and interest in the full machine learning lifecycle, including deployment of trained ML models using common frameworks (Scikit-learn, TensorFlow, PyTorch) and ideally Azure managed ones (Azure ML Workspace, Azure ML Studio) Experience in Software Engineering including programming and development of applications in Python (e.g. FastAPI more »
and deployment Understanding of and interest in the full machine learning lifecycle, including deployment of trained ML models using common frameworks (Scikit-learn, TensorFlow, PyTorch) and ideally Azure managed ones (Azure ML Workspace, Azure ML Studio) Experience in Software Engineering including programming and development of applications in Python (e.g. FastAPI more »
