6 of 6 Dimensionality Reduction Jobs in England

or TDSP methodologies for addressing commercial problems through data science or AI solutions Hands-on experience with various machine learning techniques, including but not limited to: Regression Classification Clustering Dimensionality reduction LLM Proficiency in Python for developing machine learning models and conducting statistical analyses Strong understanding of data visualization tools and techniques (e.g., Python libraries such as Matplotlib More ❯

or similar probabilistic programming tools. Hands-on experience with classical ML and modern techniques, including deep learning , transformers , diffusion models , and ensemble methods . Solid understanding of feature engineering, dimensionality reduction, model construction, validation, and calibration. Experience with uncertainty quantification and performance estimation (e.g., cross-validation, bootstrapping, Bayesian credible intervals). Familiarity with database and data processing tools More ❯

numerical and categorical modelling techniques and supervised and unsupervised machine learning methods (OLS regression and GLMs, logistic regression, KNN, SVM, decision trees/random forest, clustering and cluster analysis, dimensionality reduction, neural networks) Hands-on development experience working with version control systems (we use Git) Practical experience designing and applying data science processes to conduct experiments using a More ❯

the Business) Extensive experience (5+ years) with Python and/or SQL Proven expertise and experience of Shallow ML frameworks – regression, classification, clustering; time series forecasting (prophet, ARIMA, SARIMA); dimensionality reduction approaches Proven experience in modern code development practices and implementation of MLOps strategies in the cloud to drive operational and infrastructure cost efficiencies. Knowledge of wider data More ❯

attention to detail Proactive and delivers to timescales Desirable Attention to detail in creating documentation The ability to conduct descriptive statistics, Bayesian statistics, Inferential statistics, Probability distributions and theory, dimensionality reduction and sampling etc Strong numerical and statistical skills Additional Requirements Essential Willing to be flexible in working practices Improvement mindset - able to identify flaws in our internal More ❯

with multiomics integration, spatial transcriptomics, and related advanced sequencing technologies is highly desirable. Solid understanding of machine learning techniques, particularly in the context of biological data analysis (e.g., clustering, dimensionality reduction, predictive modeling). Experience with software development practices (e.g., version control, testing, documentation) is preferred Analytical Skills Extensive experience with bioinformatics tools, software packages, and databases used More ❯