23 of 23 XGBoost Jobs in London

data-driven solutions. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong Python skills (bonus: C++, SQL, Spark) Experience in ML algorithms (XGBoost, clustering, regression) Expertise in Time Series, NLP, Computer Vision, MLOps Knowledge of AWS/Azure/GCP, CI/CD, and Agile development Ability to own solutions and manage stakeholders More ❯

data-driven solutions. Requirements: MSc or PhD Degree in Computer Science, Artificial Intelligence, Mathematics, Statistics or related fields. Strong Python skills (bonus: C++, SQL, Spark) Experience in ML algorithms (XGBoost, clustering, regression) Expertise in Time Series, NLP, Computer Vision, MLOps Knowledge of AWS/Azure/GCP, CI/CD, and Agile development Ability to own solutions and manage stakeholders More ❯

conversion optimization, and media effectiveness. Proficiency in Python with extensive experience in data science libraries (e.g.scikit-learn, pandas, NumPy, SciPy, etc) Experience with ML frameworks such as TensorFlow, PyTorch, XGBoost, LightGBM, or similar Strong SQL skills and experience with data warehousing solutions (Snowflake, BigQuery, Redshift) Experience with cloud platforms (AWS, Azure, GCP) and their ML and AI services (SageMaker, Azure More ❯

quantitative field Deep theoretical knowledge of statistical methods and ML algorithms and their practical applications. Strong proficiency in SQL and Python, especially with core ML libraries (e.g. scikit-learn, XGBoost, SciPy, PyTorch) Extensive hands-on experience in taking advanced statistical/ML solutions from prototype to production and delivering high-impact outcomes to complex business problems Proactive technical leader with More ❯

working with structured and also unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding More ❯

compelling and actionable way Mentor junior data scientists and contribute to the evolution of data science standards and practices Key Skills & Technologies Technical: Strong in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.) Proficient in SQL for complex customer data extraction and manipulation Experience with customer analytics techniques: segmentation, RFM analysis, clustering, time-series, A/B testing, uplift modeling Familiarity More ❯

compelling and actionable way Mentor junior data scientists and contribute to the evolution of data science standards and practices Key Skills & Technologies Technical: Strong in Python (pandas, scikit-learn, XGBoost, LightGBM, etc.) Proficient in SQL for complex customer data extraction and manipulation Experience with customer analytics techniques: segmentation, RFM analysis, clustering, time-series, A/B testing, uplift modeling Familiarity More ❯

experience in the following skills: Core Data Science & Machine Learning Strong professional experience in data science, machine learning, and business analytics Hands-on experience with ML techniques such as XGBoost, deep neural networks, and transformers Practical knowledge of ML libraries and frameworks such as Fastai, Keras, TensorFlow, PyTorch, and Scikit-learn Ability to research, understand, and apply emerging machine learning More ❯

learning Proven experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data More ❯

learning Proven experience working with consumer behaviour data—ideally within healthcare, digital health, or related B2C environments Strong programming skills in Python, with experience using libraries like scikit-learn, XGBoost, and pandas Practical experience in MLOps or strong knowledge of model deployment (e.g. MLflow, Airflow, Docker, Kubernetes, model monitoring tools) Familiarity with cloud environments (AWS, GCP, or Azure) and data More ❯

Experienced working with structured and unstructured data eg. Text, PDFs, jpgs, call recordings, video, etc. Knowledge of machine learning modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, ResNets, VAEs, GANs, Markov chains, etc. Experience using specialized machine learning libraries eg. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity More ❯

stakeholders Experience of proactively contributing 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, deep learning) Experience of working More ❯

stakeholders Experience of proactively contributing 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 computational simulation/modelling highly desirable Practical knowledge and experience of developing AI solutions using advanced machine learning techniques (e.g. reinforcement learning, deep learning) Experience More ❯

in SQL, SAS (desired), Python, and the ability to write production-level code Familiarity with the most standard Python libraries used in ML (e.g., Scikit-Learn, Pandas, Numpy, LightGBM, XGBoost, just to name a few) Foster new and innovative machine-learning techniques and approaches General: Passionate for continuous learning, experimenting, and applying open-source technologies within the machine modelling space More ❯

latent class, hierarchical, and factor analysis. Understanding of working with market research and customer databases. Knowledge of statistics and machine learning applications. Experience with predictive modeling using linear models, XGBoost, discriminant analysis, etc. Beneficial Skills Experience with conjoint analysis and other pricing methods. Knowledge of GDPR and data compliance. Experience working with third-party data vendors and APIs. Some familiarity More ❯

For: 2–4 years of experience in data science, machine learning, or commercial/pricing analytics. Proficiency in Python/R, SQL , and ML libraries (e.g., scikit-learn, TensorFlow, XGBoost). Experience with data visualisation tools (Tableau, Power BI) and statistical methods. Ability to communicate insights clearly to non-technical stakeholders. Passion for applying AI/ML to solve complex More ❯

For: 2–4 years of experience in data science, machine learning, or commercial/pricing analytics. Proficiency in Python/R, SQL , and ML libraries (e.g., scikit-learn, TensorFlow, XGBoost). Experience with data visualisation tools (Tableau, Power BI) and statistical methods. Ability to communicate insights clearly to non-technical stakeholders. Passion for applying AI/ML to solve complex More ❯

Data Scientist include: 2–5 years’ experience in data science or analytics, with strong Python and SQL skills Practical knowledge of machine learning techniques and tools (e.g., scikit-learn, XGBoost) Experience working with real-world datasets and presenting insights to stakeholders Excellent communication skills and the ability to explain complex ideas clearly More ❯

Data Scientist include: 2–5 years’ experience in data science or analytics, with strong Python and SQL skills Practical knowledge of machine learning techniques and tools (e.g., scikit-learn, XGBoost) Experience working with real-world datasets and presenting insights to stakeholders Excellent communication skills and the ability to explain complex ideas clearly More ❯

high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn, XGBoost, or LightGBM Strong SQL skills for data extraction and transformation Experience working with transactional (e.g., Open Banking) and bureau data (e.g., Experian, Equifax) Expertise in feature engineering, handling class imbalance More ❯

high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn, XGBoost, or LightGBM Strong SQL skills for data extraction and transformation Experience working with transactional (e.g., Open Banking) and bureau data (e.g., Experian, Equifax) Expertise in feature engineering, handling class imbalance More ❯

full lifecycle model development, deployment and evaluation for complex problems Experience with SQL language and the following technologies: PySpark, Hadoop, Databricks Good knowledge of Linux/Bash environment Python XGBoost Good communication skills Highly skilled problem solver Exhibits a high degree of initiative At least an undergraduate degree in CS, or a STEM related field Prior experience in payment fraud More ❯

Job Description Job Role : Data & AI Manager - R&D Location : London Career Level: Manager Accenture is a leading global professional services company, providing a broad range of services in strategy and consulting, interactive, technology and operations, with digital capabilities across More ❯