1 to 25 of 27 XGBoost Jobs

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 ❯

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 ❯

products Proven experience developing cloud-based machine learning services using one or more cloud providers (preferably GCP) Excellent understanding of classical Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Strong knowledge of SQL and Python's ecosystem for data analysis (Jupyter, Pandas, Scikit Learn, Matplotlib) Strong software development skills 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 ❯

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 ❯

deliver value. Write high-quality Python code following best practices. Continuously research and apply new tools, techniques, and technologies. Experience with: Cloud deployment,Neural networks and libraries like TensorFlow, XGBoost, CatBoost, SKlearn, API development, SQL,CI/CD, DevOps, or MLOps pipelines Experience with: Strong hands-on experience or genuine interest in data science and analytics. Proficiency in Python and More ❯

key machine learning models, including 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 - you should be happy working More ❯

and collaborative team player. Experience as a lead developer tackling complex problems at scale. Experience mentoring junior engineers. Familiarity with various machine learning frameworks and toolkits (e.g., scikit-learn, XGBoost, TensorFlow). Hands-on experience building GenAI solutions using patterns such as Retrieval-Augmented Generation (RAG) or fine-tuning Large Language Models (LLMs). Have experience with cloud computing platforms. More ❯

e-commerce - this is essential as you'll be the domain expert from day one. Excellent Python programming skills and strong familiarity with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras etc. Proven track record deploying ML models to production (API, batch, or streaming contexts) Solid understanding of the modern software engineering, infrastructure and data technologies Experience working 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 ❯

compelling analysis findings to clients and senior stakeholders Requirements: Proven ability to deliver ML solutions that drive real business value Strong Python/ML stack skills (e.g., scikit-learn, XGBoost, TensorFlow, etc.) Experience working with clients and/or stakeholders – you’re comfortable in a consulting setting Ideally available on a shorter notice period **Please note that this role does 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 ❯

applications powered by Large Language Models and leading their implementation. Experience working with recommendation engines, data pipelines, or distributed machine learning. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch, XGBoost). Knowledge of data warehousing concepts, including data warehouse technical architectures, infrastructure components, ETL/ELT and reporting/analytic tools and environments (e.g., Apache Beam, Hadoop, Spark, Pig, Hive More ❯

others, shares knowledge, and promotes best practices. Excellent communicator, able to work cross-functionally and tailor messages to different audiences. Hands-on expertise in Python, SQL, ML frameworks (e.g. XGBoost, TensorFlow, PyTorch), and cloud tools (GCP, BigQuery, Vertex AI). Familiar with generative AI tools and frameworks (e.g. OpenAI, HuggingFace, LangChain). Deeply curious, commercially minded, and impact-driven with More ❯

services) Timeseries forecasting Solid understanding of computer science fundamentals, including data structures, algorithms, data modelling and software architecture Strong knowledge of Machine Learning algorithms (e.g. Logistic Regression, Random Forest, XGBoost, etc.) as well as state-of-the-art research area (e.g. NLP, Transfer Learning etc.) and modern Deep Learning algorithms (e.g. BERT, LSTM, etc.) Machine Learning Engineer, timeseries, forecasting, VertexAI More ❯

GCP (BigQuery, Vertex AI, Cloud Run) Strong SQL complex querying Python for analytics, backend logic, and model prototyping Familiarity with LLM APIs , prompt engineering , embeddings , and traditional ML (e.g. XGBoost , scikit-learn ) Comfortable deploying tools using Docker , Flask/FastAPI , and GCP services Ability to work independently and iterate quickly toward high-quality outcomes Full-stack data capability, from pipelines More ❯