in the AI Lab. Responsibilities Develop new ML models and AI techniques Lead on research projects within a global team Review relevant AI/ML literature to identify emerging methods, technologies, and best practices. Explore new data sources and discover techniques for best leveraging data Minimum Qualifications A Master's or PhD in a field related to AI/… disciplines Strong background applying Deep Learning techniques (including implementing custom architectures, optimizing model performance, developing novel loss functions, metrics, and benchmarks, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning (e.g. Bayesianmethods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, PyTorch Lightning, or similar frameworks Strong More ❯
audiences. Bonus: Proficiency in Python, our primary programming language. Machine learning model development and evaluation experience Experience with SQL and business intelligence tools such as Looker. Understanding of Bayesian statistics. Experience building or maintaining data pipelines. Snowflake/dbt experience is particularly valuable. Experience using LLM APIs in a production environment. The salary We expect to pay More ❯
is essential. Experience with Regression based models in an MMM context. Strong understanding of statistical modelling/Machine Learning techniques. Experience with probabilistic programming andBayesianmethods Good working knowledge of cloud-based data science frameworks. This is a 6 month contract position which provides a daily rate of £688 (Inside IR35). In terms of More ❯
City of London, London, United Kingdom Hybrid/Remote Options
Ventula Consulting
is essential. Experience with Regression based models in an MMM context. Strong understanding of statistical modelling/Machine Learning techniques. Experience with probabilistic programming andBayesianmethods Good working knowledge of cloud-based data science frameworks. This is a 6 month contract position which provides a daily rate of £688 (Inside IR35). In terms of More ❯
and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models andBayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯
and externally. Continuously develop your own AI/ML and engineering skills. Essential skills and experience Academic or industrial research experience in machine learning, especially probabilistic models andBayesian statistics. Proficiency in designing and programming advanced ML algorithms. Ability to apply state-of-the-art research to real-world problems. Proficiency in operating and evolving advanced ML More ❯
level Python programming (NumPy, PyTorch/TensorFlow, SciPy, pandas) Deep expertise in time-series and sequence modelling (RNNs, LSTMs, transformers, attention mechanisms) Strong foundation in probabilistic models (HMMs, Bayesian inference, graphical models) Track record of delivering impactful research or production systems What's in it for me? Salary of £80,000 - £100,000 dependent on experience Work More ❯
level Python programming (NumPy, PyTorch/TensorFlow, SciPy, pandas) Deep expertise in time-series and sequence modelling (RNNs, LSTMs, transformers, attention mechanisms) Strong foundation in probabilistic models (HMMs, Bayesian inference, graphical models) Track record of delivering impactful research or production systems What's in it for me? Salary of £80,000 - £100,000 dependent on experience Work More ❯
experience within predictive modelling, machine learning, and probability theory. Ideally this would be within sports or gaming/betting industries. Understanding of techniques such as Monte Carlo simulation, Bayesianmodelling, GLMs, mixed effects models, time series forecasting etc Strong programming ability, preferably in Python SQL and relational databases The company offer some great benefits including a bonus More ❯
team in technical discussions, customer workshops, and industry events. What You’ll Bring 🔥 Deep expertise in ML, statistical modelling, and modern AI techniques (supervised/unsupervised, time-series, Bayesian, deep learning). 🐍 Strong Python engineering skills — NumPy, Pandas, Scikit-Learn, plus PyTorch/TensorFlow. 🏗 Experience building scalable ML systems in production (ML Ops, CI/CD for More ❯
team in technical discussions, customer workshops, and industry events. What You’ll Bring 🔥 Deep expertise in ML, statistical modelling, and modern AI techniques (supervised/unsupervised, time-series, Bayesian, deep learning). 🐍 Strong Python engineering skills — NumPy, Pandas, Scikit-Learn, plus PyTorch/TensorFlow. 🏗 Experience building scalable ML systems in production (ML Ops, CI/CD for More ❯
tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. BayesianModelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯
City of London, London, United Kingdom Hybrid/Remote Options
Singular Recruitment
tracking, positiona l), and libraries like mplsoccer Advanced MLOps & Modelling : Experience with the Vertex AI ecosystem, especially pipelines, and advanced techniques such as player valuation , tactical modelling , etc. BayesianModelling : Knowledge of probabilistic programming (e.g., PyMC ) for uncertainty-aware predictions Stakeholder Collaboration : Demonstrated ability to work directly with stakeholders to scope, iterate, and deliver impactful solutions in More ❯
junior team members, leading research projects, and guiding collaborative efforts is a plus. Knowledge of the following machine learning domains is a plus. Generative models leveraging diffusion or Bayesian Flow Networks. Large-scale distributed machine learning training. Knowledge, experience or interest in the following biological domains is a plus. Drug discovery and protein engineering. Understanding of protein More ❯
to be successful, you will have the following experience: Strong Data Analyst or Data Science background, with experience within Python and AI/ML technologies Machine learning andBayesianmodelling experience is highly desirable Experience of working with the Home Office as a customer SC Clearance is essential Within this role, you will be responsible for: Analyse More ❯
to be successful, you will have the following experience: Strong Data Analyst or Data Science background, with experience within Python and AI/ML technologies Machine learning andBayesianmodelling experience is highly desirable Experience of working with the Home Office as a customer SC Clearance is essential Within this role, you will be responsible for: Analyse More ❯
including credit, collections, and data engineering—to translate business objectives into robust analytical solutions. Build software using modern technology to enable investing and asset management at scale. Apply Bayesianmodellingand probabilistic programming techniques to address uncertainty and improve prediction accuracy. Analyse large-scale datasets to identify key drivers, trends, and early warning signals within NPL portfolios. … integrating new techniquesand tools. Requirements: University degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred. Strong expertise in statistical modelling, Bayesian inference, and machine learning. Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan) Experienced in SQL. Ability to write efficient and robust queries. More ❯
including credit, collections, and data engineering—to translate business objectives into robust analytical solutions. Build software using modern technology to enable investing and asset management at scale. Apply Bayesianmodellingand probabilistic programming techniques to address uncertainty and improve prediction accuracy. Analyse large-scale datasets to identify key drivers, trends, and early warning signals within NPL portfolios. … integrating new techniquesand tools. Requirements: University degree in a STEM field (e.g., Mathematics, Statistics, Computer Science, Engineering, Physics, Economics); advanced degree preferred. Strong expertise in statistical modelling, Bayesian inference, and machine learning. Proficient in Python (using libraries such as NumPy, pandas, scikit-learn, PyMC or Stan) Experienced in SQL. Ability to write efficient and robust queries. More ❯
as a trusted advisor to clients, working closely with senior stakeholders to shape strategy and deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). 🚀Strong More ❯
as a trusted advisor to clients, working closely with senior stakeholders to shape strategy and deliver measurable business outcomes. What You’ll Bring 🔥Deep knowledge of ML/statistical methods (e.g. supervised/unsupervised, Bayesian, time-series). ⚙️Strong Python skills with core libraries (NumPy, Pandas, Scikit-Learn) plus deep learning frameworks (PyTorch, TensorFlow). 🚀Strong More ❯
