quantitative 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 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 »
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 »
London, England, United Kingdom Hybrid / WFH Options
Morgan McKinley
environment. Systems/Internal Processes Familiarity with programming languages such as Python, R or Java and with data analysis libraries (e.g. Pandas, NumPy, scikit-learn). Understanding of database technologies (ETL) and SQL proficiency for data manipulation, data mining and querying. Knowledge of Big Data Tools (Spark or more »
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). Solid understanding of quantitative finance concepts, including asset pricing, risk management, and portfolio optimization. Excellent problem-solving skills and the ability to more »
a related field. Experience in AI/Machine Learning research and development. Proficiency in Python. Experience with popular machine learning frameworks (TensorFlow, PyTorch, scikit-learn). Experience with using NVIDIA GPUs for fine tuning AI models Strong mathematical and statistical background. Excellent problem-solving and critical-thinking skills. 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 »
NLP , and LLMs Expert ability with ML/MLOps Experience mentoring/up-skilling more junior team members. Strengths in SQL , Python ( Pandas , Scikit - Learn , PyTorch ) PhD -level education and experience within Marketing is preferred. Experience in an academic/research background. If you think this opportunity could 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 »
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 »
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 »
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 »
scientists Proficiency in data forecasting, analysis, prediction, and deriving trading signals from datasets. Extensive hands-on experience with TensorFlow (and/or Keras), scikit-learn, and related tools, coupled with a strong command of Python. Robust analytical and mathematical abilities essential for model development and validation. Exceptional problem 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 »
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 »
associated security considerations. Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. more »
associated security considerations. Previous experience with ML, LLM, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn is desirable. Experience in implementing secure coding practices, DevOps, CI/CD pipelines and familiarity with secure software development life cycle (SDLC) methodologies. 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 »
effectively. Technical Requirements To succeed in this role, you should have: Understanding of the full machine learning lifecycle and experience with frameworks like Scikit-learn, TensorFlow, or PyTorch. Demonstrable experience mentoring junior team members. Knowledge of probability, statistics, and common machine learning techniques. Experience in software engineering, particularly 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 »
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 »
building and maintaining cloud Data Warehouses 2+ years’ experience of Snowflake configuration, deployment and maintenance Extensive hands-on experience of using Python commercially (scikit-learn, pandas, numpy, etc.) Extensive hands-on experience of using Azure to import, store, process and archive data If you feel your experience is more »
