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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
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 ❯
