Scientist, 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. more »
Data Scientist or similar role Proficiency in programming languages such as Python or R, along with libraries/frameworks such as TensorFlow, PyTorch, Scikit-learn, or Pandas. Strong knowledge of statistical analysis, hypothesis testing, and experimental design. Experience with SQL databases, data warehousing, and big data technologies. Familiarity more »
retrieval. Demonstrate proficiency in programming languages including Python, Spark, Databricks, Pyspark, SQL, and ML Algorithms. Implement Machine Learning models and algorithms using Pyspark, ScikitLearn, and other relevant tools. Manage Azure DevOps, CI/CD pipelines, GitHub, and Kubernetes (AKS) for efficient software development and deployment. Implement ML 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 »
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 »
methods for strategy parameter optimization Prior experience at a top tier hedge fund, proprietary trading house or investment bank Exposure to pandas, numpy, scikit-learn, statsmodels-tsa, TensorFlow, Keras, and Matplotlib libraries more »
of professional experience as a python software engineer, preferably in the biotech or healthcare industry- Proficiency in broader Python ecosystem Django, NumPy, pandas, scikit-learn, TensorFlow, PyTorch, etc.- Experience in machine learning, data science, and data visualization, using tools such as Jupyter, matplotlib, seaborn, plotly, etc.- Knowledge of more »
years in a managerial role overseeing a team of engineers. Proficiency in Python and experience with relevant libraries and frameworks (e.g., TensorFlow, PyTorch, Scikit-learn). Strong understanding of data science principles, predictive modelling, and advanced analytics. Excellent problem-solving skills and the ability to think critically and 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 »
models. Experience in manipulating and interpreting data from disparate sources. Proficient in Python coding and core data science libraries, such as Pandas, TensorFlow, Scikit-learn etc. Experience with Cloud Computing (AWS, GCP, Azure) - Ideally in AWS. Creativity and innovative thinking to explore diverse data sources for improved predictive more »
Our client is a leading fintech company dedicated to revolutionizing the financial services industry. They leverage advanced analytics, machine learning, and cutting-edge technology to deliver innovative financial solutions to their clients. Their mission is to make financial services more more »
constantly evolving set of systems, tools, and libraries. Most of our code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the open-source libraries we use extensively. We implement the systems that require the highest data throughput in more »
City Of London, England, United Kingdom Hybrid / WFH Options
RJC Group
methods (SQL, GraphQL, APIs) Beneficial Requirements Experience around data science tools and algorithms Manipulation technologies (e.g., WebSockets, Kafka, Spark) TensorFlow, Pandas, pySpark and scikit-learn would be great Salary up to £75K + 20% bonus and benefits package We have interview slots lined up for later this week 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 »
guide):Understanding of and interest in the full machine learning lifecycle, including deploying trained machine learning models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorchDemonstrable experience of managing/mentoring more junior members of the team Understanding of the core concepts of probability and statistics more »
manner -Must know CI/CD pipelines and Agile frameworks , preferably with the MLOps context . -Understanding or familiar with technologies such as: Scikit-Learn, TensorFlow, Torch, ChatGPT, Llama, LangChain (or equivalent), RAG, Model Security, Jupyter Notebook/JupyterLab, Unit Testing, Integration Testing, E2E Testing, ETL/ELT more »
in machine learning engineering. Proven expertise in regression modelling and time series modelling. Numpy/Pandas/Keras/Tensorslow/XGBoost/Scikit-learn Experienced in GCP preferably Extensive background in deploying and productionizing machine learning models. Strong programming skills in languages such as Python, R, or more »
looking to add experts to the machine learning team! The best-matched machine learning engineer will have the following experience and abilities: Tech: Python (ScikitLearn, Pandas, Numpy, Scipy) and GCP Hybrid working in London, 3 days a week in the office Desirable: experience mentoring junior team members and reviewing code more »
Quantitative Analyst Sports Trading and Analytics Company Hybrid - 3 days office, 2 days WfH Up to £80,000 + bonus About the company A proprietary trading firm and alternative investment manager with a primary focus in quantitative and fundamental sports more »
Glasgow, Scotland, United Kingdom Hybrid / WFH Options
Eden Scott
Our client an innovative designer and manufacturer of ground-breaking products and solutions is looking for a Software Engineer to join their team. You will work in a small software team collaborating with highly skilled colleagues contributing to the fast more »
security 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 »
SENIOR DATA SCIENTIST Customer & Marketing 💰£550 - £600 per day ⏰ 3 months + 🏠 Hybrid/London 📌Work across a range of clients in retail, telco, automotive and healthcare industries 📌Deliver a range of machine learning and AI solutions to support omnichannel more »
and ensemble models.Experience in manipulating and interpreting data from disparate sources.Proficient in Python coding and core data science libraries, such as Pandas, TensorFlow, Scikit-learn etc.Experience with Cloud Computing (AWS, GCP, Azure) – Ideally in AWS.Creativity and innovative thinking to explore diverse data sources for improved predictive models.Desirable:Experience more »
deployment of complex machine learning solutions. Expertise in product experimentation, Causal AI, and advanced statistical techniques. Deep knowledge of data science tools (e.g., scikit-learn, TensorFlow, PyTorch) and big data technologies (e.g., Spark). Proficiency in Python for data manipulation, model building, and scripting. Strong communication skills to more »
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 »
