1 to 25 of 38 Linear Regression Jobs in England

Engineering (MSc may be considered).**Experience:*** 5–6 years of significant professional experience in Data Science.**Expertise in Machine Learning:*** Proficient in both supervised and unsupervised learning.* Techniques: Linear and logistic regressions, random forests, gradient boosting, neural networks (RNN, LSTM, CNN), text mining, topic extraction, NLP, K-Means, decision trees.* Applications: Computer vision, Generative AI, Language Models (e.g. More ❯

statistical analyses leading to the understanding of the structure of data sets. Proven and demonstrable experience with at least three of the following machine learning algorithms: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization. Experience working with Java and Python, and strong understanding of More ❯

statistical analyses leading to the understanding of the structure of data sets. Proven and demonstrable experience with at least three of the following machine learning algorithms: neural networks, logistic regression, non-linear regression, random forests, decision trees, support vector machines, linear/non-linear optimization. Experience working with Java and Python, and strong understanding of More ❯

quantitative researcher, quantitative analyst or another relevant role Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression More ❯

Direct message the job poster from Harnham Building Data Science and Machine Learning Teams in the UK | The Talent Driving The Data and AI Revolution Data Scientist - (Forecasting/Regression) Remote (UK-Based) Up to £45,000 The Company This UK-based start-up has grown rapidly in just two years. With a team of approximately 30 people, they … you’ll develop and refine KPI prediction models, working with real-world data to generate actionable insights. Clean and process data to ensure accuracy and usability. Build and maintain linear regression models for KPI tracking. Access APIs and integrate software tools to improve workflows. Collaborate with the revenue team to produce insightful reports. Support internal product development by … They're Looking For 1-2 years of experience in data science or a related field, or a Master’s degree. Strong Python skills (essential), SQL, and experience with linear regression/statistical modeling. Experience with web scraping, machine learning, or dashboarding is a plus. A background in finance or familiarity with financial data is advantageous but not More ❯

sensor and assay performance data Implement multivariate computational models (e.g., Principal Component Analysis (PCA), Partial Least Squares (PLS)) to identify key measurement variables within complex electrochemical datasets. Develop non-linear regression models to improve the accuracy of immunoassay data analysis. Apply machine learning techniques, including Random Forest and neural networks, to classify sample types based on electrochemical measurements … in computational modelling, data analysis, and machine learning techniques. Proficiency in Python, R, MATLAB, or other statistical programming languages. Knowledge of multivariate analysis techniques (e.g., PCA, PLS) and non-linear regression models. Experience developing predictive machine learning algorithms (e.g., Random Forest, Neural Networks). Proficiency in SQL (preferably MySQL) and database management for engineering data storage Experience working More ❯

data scientist, quantitative researcher, quantitative analyst or another relevant roleDegree in Applied Mathematics, Computer Science, Financial Engineering, Technology or EngineeringKnowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methodsExperience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree More ❯

Numeric degree ideally to Masters level (min 2:1) Working knowledge of Python, Pandas, NumPY, PyTest, Java and R Understanding of machine learning techniques, such as clustering, classification, and regression Previous experience presenting information to key stakeholders Nice to haves...... Previous experience using Generalised Linear Regression Modelling Knowledge of Bayesian Statistics and Monte Carlo Simulation Experience with More ❯

Numeric degree ideally to Masters level (min 2:1) Working knowledge of Python, Pandas, NumPY, PyTest, Java and R Understanding of machine learning techniques, such as clustering, classification, and regression Previous experience presenting information to key stakeholders Nice to haves...... Previous experience using Generalised Linear Regression Modelling Knowledge of Bayesian Statistics and Monte Carlo Simulation Experience with More ❯

engineering on large datasets, conduct exploratory data analysis, and build models using time series forecasting techniques such as ARIMA, ARIMAX, Holt Winter, and ensemble methods. Apply supervised learning algorithms (linear/logistic regression) and unsupervised algorithms (k-means, PCA, market basket analysis). Solve optimization problems related to inventory and network optimization, with hands-on experience in linear … CS, Math, ML, Stats, Operations Research). Proficiency in Python, R, or similar scripting languages; experience with SQL, MySQL, and databases. Expertise in machine learning, statistics, and optimization, including linear programming. Experience with statistical measures such as hypothesis testing, confidence intervals, and error analysis. Excellent communication skills for technical and non-technical audiences. Preferred additional skills include experience with More ❯

across the platform to support commercial growth and marketing optimisation. Deliver pre- and post-campaign analysis, segmentation work, and ongoing performance tracking. Build and deploy statistical models such as linear regression, clustering, forecasting, and advanced A/B tests. Work closely with ML Engineers, commercial teams, and senior stakeholders to translate insight into business action. Support marketing measurement … science, or advanced analytical modelling. Hands-on experience using Python for statistical analysis and modelling. Advanced SQL skills for data extraction and manipulation. Experience applying statistical methods such as linear regression, KMM, forecasting models, and experimentation. Strong communication skills with the ability to simplify complex analysis for business audiences. Degree in Mathematics, Statistics, Economics or related quantitative field. More ❯

You’ll Need: Proven success with profitable trading strategies. Strong programming skills in C Python in a Linux environment. Working knowledge of forecasting and data mining techniques, such as linear and non-linear regression analysis, neural networks, or support vector machines. Strong experience developing statistical models in a trading environment. Proven success working with large data sets More ❯

science role. Degree in a highly quantitative field: Computer Science, Machine Learning, Statistics, Mathematics, etc. Proficiency with data mining, knowledge of probability theory and advanced statistical techniques. Experience with regression analysis (beyond linear regression), supervised learning, unsupervised learning or time-series analysis. Experience with scientific scripting languages (Python, R, Matlab). Experience accessing and manipulating data in More ❯

analysis and metrics into actionable insights for the advertiser and both technical and non-technical stakeholders In depth understanding of advanced statistical techniques and methodologies as well as simple linear regression analysis, multivariate regression analysis and model building Advanced in SQL ability to write complex queries from scratch from multiple tables Fluency with Python (or R) – ability More ❯

massive datasets, effective exploratory data analysis, and model building using industry standard time Series Forecasting techniques like ARIMA, ARIMAX, Holt Winter and formulate ensemble model. Proficiency in both Supervised (Linear/Logistic Regression) and Unsupervised algorithms (k means clustering, Principal Component Analysis, Market Basket analysis). Experience in solving optimization problems like inventory and network optimization. Should have … hands on experience in Linear Programming. Work closely with internal stakeholders like the business teams, engineering teams and partner teams and align them with respect to your focus area. Detail-oriented and must have an aptitude for solving unstructured problems. You should work in a self-directed environment, own tasks and drive them to completion. Excellent business and communication More ❯

and experience with financial systems (e.g., Bloomberg, Reuters, or similar). Familiarity with accounting principles (e.g., IFRS, GAAP) and regulatory requirements (e.g., Basel III, IFRS 9). Statistical Techniques: Linear & Logistic Regression, Hypothesis Testing, Exploratory Data Analysis, Survival Analysis, Cluster Analysis, various Statistical Tests and Cross-Validation Techniques, ML Algorithms. Proficiency in programming languages like Python, R, or More ❯

You'll Need: Proven success with profitable trading strategies. Strong programming skills in C Python in a Linux environment. Working knowledge of forecasting and data mining techniques, such as linear and non-linear regression analysis, neural networks, or support vector machines. Strong experience developing statistical models in a trading environment. Proven success working with large data sets More ❯

analysis and metrics into actionable insights for the advertiser and both technical and non-technical stakeholders - In depth understanding of advanced statistical techniques and methodologies as well as simple linear regression analysis, multivariate regression analysis and model building - Advanced in SQL ability to write complex queries from scratch from multiple tables - Fluency with Python (or R) - ability More ❯

analysis and metrics into actionable insights for the advertiser and both technical and non-technical stakeholders - In depth understanding of advanced statistical techniques and methodologies as well as simple linear regression analysis, multivariate regression analysis and model building - Advanced in SQL with the ability to write complex queries from scratch from multiple tables - Fluency with Python (or More ❯

and experience with financial systems (e.g., Bloomberg, Reuters, or similar). Familiarity with accounting principles (e.g., IFRS, GAAP) and regulatory requirements (e.g., Basel III, IFRS 9). Statistical Techniques: Linear & Logistic Regression, Hypothesis Testing, Exploratory Data Analysis, Survival Analysis, Cluster Analysis, various Statistical Tests and Cross-Validation Techniques, ML Algorithms. Proficiency in programming languages like Python, R, or More ❯

Their insights empower investors to make informed decisions by providing performance data ahead of public reports. Responsibilities: Clean and process data to ensure accuracy and usability. Build and maintain linear regression models for KPI tracking. Access APIs and integrate software tools to enhance workflows. Collaborate with the revenue team to generate insightful reports. Support internal product development by … improving data pipelines and analysis. Requirements: 1-2 years in data science or a related field, or a Master’s degree. Strong Python programming (essential), SQL, and linear regression/statistical modelling. Experience with web scraping, machine learning, or dashboarding is a plus. A background in finance or exposure to financial data is advantageous but not required. How More ❯

Markdown documentation for building, testing, and deploying. Cloud : Leverage cloud infrastructure (e.g., AWS EC2), databases, and configuration with markup files for remote management and deployment. Model : Implement models (e.g., linear regression, gradient boosting) with training/testing datasets, cross-validation, performance visualisation, and use hosted APIs; explore techniques like time-series forecasting, clustering, or Bayesian inference. Orchestration and More ❯

enhance statistical processes, and partner with internal and external stakeholders to deliver data-driven solutions. Python. Git for version control. Classical statistics. Hypothesis testing (parametric and non-parametric). Linear or logistic regression models. Exposure to small datasets, not just large (very important). Familiarity with pharma/health/medical datasets. Mixed effects models – ability to use More ❯

Expertise in T-SQL to write complex queries and stored procedures. Understanding of database optimisation, data mining, auditing, and segmentation. Skilled in data visualisation and statistical techniques such as linear regression. Ability to conduct user acceptance testing and ensure data integrity. Confidence to challenge existing processes and recommend improvements. Effective communication skills and the ability to translate complex data More ❯

The Role: Data Cleaning and Preparation: Collect, clean, and prepare large media datasets from various sources (CRM, ad servers, audience panels) for analysis. Statistical Analysis: Utilise econometric techniques like regression analysis, time series modelling, and panel data analysis to identify relationships between media spend and business outcomes. Model Validation and Interpretation: Evaluate the accuracy and robustness of models, interpret … Data Science: Proficient in programming languages like Python, R, and SQL including data manipulation, data imputation, statistical modelling, and visualisation libraries. Econometrics Background Useful: Expertise in statistical methods like linear regression, generalised linear models, panel data analysis, and time series forecasting. Media Industry Knowledge: Understanding of media landscape, ad formats, audience measurement, and industry KPIs. Communication Skills More ❯