to stand out? Consulting Experience Databricks Machine Learning Associate or Machine Learning Professional Certification. Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc. Experience with deep learning frameworks like TensorFlow or PyTorch. Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time 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 ❯
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 More ❯
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 More ❯
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 More ❯
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 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 ❯
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 ❯
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 ❯
Manchester, Lancashire, United Kingdom Hybrid / WFH Options
MAG (Airports Group)
SageMaker and Lambda, and you'll know your way around Git, SQL, and common Python data science libraries (like pandas/polars, scikit-learn, xgboost/lightGBM, and TensorFlow/PyTorch). Bonus points if you've worked with linear programming, or have experience in time series forecasting, agent-based More ❯
track record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in More ❯
london, south east england, United Kingdom Hybrid / WFH Options
Oliver Bernard
track record delivering ML/AI solutions in complex, real-world environments Strong Python skills and experience with key ML libraries (e.g., scikit-learn, XGBoost, PyTorch) Exposure to Generative AI technologies (e.g., LLMs, embeddings, RAG systems) Excellent communication skills and ability to engage senior stakeholders Nice to Have: Experience in More ❯
While they use a range of technologies internally, familiarity with open-source tools is highly valued. Languages & Libraries: Python, R, Pandas, NumPy, scikit-learn, XGBoost, LightGBM, statsmodels NLP & ML Frameworks: spaCy, Hugging Face Transformers, TensorFlow or PyTorch (where applicable) Data Engineering & Pipelines: dbt, Airflow, SQL, Spark, Dask Visualisation: Plotly, Seaborn More ❯
City, Edinburgh, United Kingdom Hybrid / WFH Options
ENGINEERINGUK
Python. Significant experience with SQL (e.g., RDBMS, Spark, Presto, or BigQuery). Experience with machine learning, optimization, and data manipulation tools (e.g., scikit-learn, XGBoost, cvxpy, Pandas, Spark, or PyTorch). Experience with at least one low-level or scientific language (e.g., C, Rust, Go, Julia, or R). Experience 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 ❯
or market modelling, preferably in insurance. Proficiency in Python and SQL for data analysis and model development. Hands-on experience with machine learning frameworks (XGBoost, LightGBM, etc.). Strong understanding of market dynamics, elasticity modeling, and demand forecasting. Experience in deploying models into production and integrating them with business decision 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 ❯
executing, and analysing complex experiments end-to-end. Hands-on experience with statistical techniques (e.g., regressions, matching) and machine learning models (e.g., Naive Bayes, XGBoost). Strong Python and SQL skills, including writing reusable, standardised code and working in analytical environments like Snowflake. Experience conducting exploratory data analysis, including visualisations More ❯
data privacy regulations, model security, and designing solutions that are compliant with industry standards. Background in machine learning libraries such as TensorFlow, PyTorch, or XGBoost for model development and training. Familiarity with serverless computing for ML workflows using AWS Lambda and API Gateway, and multi-cloud environments. If you are More ❯
Why loveholidays? At loveholidays, we're on a mission to open the world to everyone, giving our customers' unlimited choice, unmatched ease and unmissable value for their next getaway. Our team is the driving force behind our role as our More ❯
Why loveholidays? At loveholidays, we're on a mission to open the world to everyone, giving our customers' unlimited choice, unmatched ease and unmissable value for their next getaway. Our team is the driving force behind our role as our More ❯
