LOTUS HR | Executive Recruitment & Leadership Coaching van C-Suite en Management
years of relevant experience in a data science/ML engineering role Expert in Python and key libraries (Scikit-learn, Pandas, PyTorch, TensorFlow, XGBoost, Transformers) Strong understanding of statistics, ML algorithms, and data wrangling Familiarity with cloud platforms (Azure, AWS, GCP) and containerized workflows (Docker, Kubernetes) Knowledge of ethical and More ❯
computer science fundamentals, including data structures, algorithms, data modelling, and software architecture Solid understanding of classical Machine Learning algorithms (e.g., Logistic Regression, Random Forest, XGBoost, etc.), state-of-the-art research areas (e.g., NLP, Transfer Learning, etc.), and modern Deep Learning algorithms (e.g., BERT, LSTM, etc.) Solid knowledge of SQL More ❯
York, Yorkshire, United Kingdom Hybrid / WFH Options
Method Resourcing Solutions Ltd
in data science within financial services, insurance, or E-commerce (not essential). Familiarity with cloud-based deployment. Knowledge of neural networks, TensorFlow, CatBoost, XGBoost, SKlearn, or Pandas. Experience with API development. Proficiency in SQL. Background in software engineering or DevOps/MLOps. Understanding of CI/CD pipelines. Why More ❯
Manchester, Lancashire, United Kingdom Hybrid / WFH Options
Method Resourcing Solutions Ltd
in data science within financial services, insurance, or E-commerce (not essential). Familiarity with cloud-based deployment. Knowledge of neural networks, TensorFlow, CatBoost, XGBoost, SKlearn, or Pandas. Experience with API development. Proficiency in SQL. Background in software engineering or DevOps/MLOps. Understanding of CI/CD pipelines. Why More ❯
to the design, development, testing, and deployment of data science and AI solutions Experience and understanding of applied machine learning techniques in Python (e.g., xgboost, regression, decision trees) Experience with physics modelling highly desirable Practical knowledge and experience of developing AI solutions using advanced machine learning techniques (e.g., reinforcement learning More ❯
Leeds, England, United Kingdom Hybrid / WFH Options
Protect Group
the organisation. Required Skills & Experience: Extensive experience conducting data analysis within relevant sectors. Proficiency in SQL, Python, and data science libraries such as sklearn, XGBoost, and CatBoost. Experience with Azure, MLOps, and API frameworks. Strong understanding of statistical methods, probability theory, pricing optimisation, and elasticity modelling. Expertise with data visualisation More ❯
bradford, yorkshire and the humber, united kingdom Hybrid / WFH Options
Protect Group
the organisation. Required Skills & Experience: Extensive experience conducting data analysis within relevant sectors. Proficiency in SQL, Python, and data science libraries such as sklearn, XGBoost, and CatBoost. Experience with Azure, MLOps, and API frameworks. Strong understanding of statistical methods, probability theory, pricing optimisation, and elasticity modelling. Expertise with data visualisation More ❯
fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯
fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯
fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯
fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯
fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯
london (city of london), south east england, united kingdom
In Technology Group
fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯
fresh ideas to the table What we’re looking for: Strong Python skills and experience in ML libraries like scikit-learn, PyTorch, TensorFlow , or XGBoost Hands-on experience building and deploying ML models into production environments Familiarity with ML Ops workflows (e.g., MLflow, Airflow, Weights & Biases, or Kubeflow) Experience working More ❯
Requirements Proven experience as a Machine Learning Engineer or similar role Strong proficiency in Python and ML libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, etc. Hands-on experience with data pipelines, model training, evaluation, and deployment Solid understanding of statistics, data structures, and algorithms Familiarity with cloud platforms (e.g. More ❯
science or machine learning role; startup experience preferred. Strong coding skills in Python (and/or R); deep familiarity with libraries like scikit-learn, XGBoost, PyTorch, TensorFlow . Strong grasp of probability theory, statistical inference, and A/B testing . Experience with causal inference and online learning methodologies. Proficiency More ❯
Python and SQL through Git, and applying other best practices to technical projects Experience and understanding of applied machine learning techniques in Python (e.g. xgboost, regression, decision trees) Practical knowledge and experience of developing AI solutions using advanced machine learning techniques (e.g. reinforcement learning, deep learning, LLMs) Experience of using More ❯
trees, and other traditional machine learning models, translating conceptual ideas into actual solutions. Fluent in some of these machine learning frameworks such as SKLearn, XGBoost, PyTorch, or Tensorflow. Proficient in Python and able to transform abstract machine learning concepts into robust, efficient, and scalable solutions. Strong Computer Science fundamentals and More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Peregrine
statistics Experience of data science in finance, insurance or Ecommerce is an advantage but not required. Experience with neural networks and Tensor Flow, CatBoost, XGBoost, SKlearn, Pandas If you hold the experience and technical skills outlined above which would enable you to hit the ground running, please apply to find More ❯
Gradient Boosting Machines (GBMs), Neural Networks and Large language models (LLMs). Hands-on experience with popular machine learning libraries such as Scikit-learn, XGBoost, LightGBM, TensorFlow, or PyTorch. Knowledge of AWS products and services including Sagemaker. Deep knowledge of Microsoft Excel in a commercial setting. You enjoy being Agile More ❯
new tools and packages where appropriate. Desired Skills & Experience: Core Technical Skills Expert in Python, SQL, and modern data science toolkits (e.g. scikit-learn, XGBoost, statsmodels). Solid grasp of dbt for data transformation. Experience with modern cloud data stacks - Snowflake, BigQuery, Redshift, etc. Comfortable working in agile environments with More ❯
basics but by year 3 should be quite proficient with at least pulling data Data Lake implementation and processing. Knowledge of Snowflake or equivalent XGBoost, LightGBM and the ability to use them for tabular data NLP and familiar with modern transformers Experience using Tableau or PowerBI for visualisations and reporting More ❯
into business workflows. Desirable: Background in quantitative disciplines (math, stats, physics). Experience in finance, insurance, or ecommerce. Familiarity with ML frameworks like TensorFlow, XGBoost, and SKLearn. If this sounds like something you are interested in, please get in contact: thomas.deakin@spgresourcing.com SPG Resourcing is an equal opportunities employer and More ❯
