1 to 25 of 40 Linear Regression Jobs in England

Proficiency: Strong skills with libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Ability to write clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests), clustering (k-means, DBSCAN), and time-series forecasting (ARIMA, Prophet). Model evaluation, tuning, and deployment. Business Requirement More ❯

Python Proficiency: Strong coding skills using libraries like pandas, NumPy, scikit-learn, PyTorch, and Hugging Face Transformers. Writing clean, modular, and testable code. Traditional Machine Learning Models: Experience with regression (linear, ridge), classification (logistic regression, decision trees, random forests), clustering (k-means, DBSCAN), and time-series forecasting (ARIMA, Prophet). Model evaluation, tuning, and deployment. Business Requirement More ❯

Science (2:1 and above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with a preference for SQL and Python. Familiarity with large language models and More ❯

Science (2:1 and above). Strong numerical background with a knowledge of key statistical principals e.g. Bayesian and frequentist statistics, probability distributions. Fundamental understanding of ML algorithms e.g. linear and logistic regression, random forest, neural networks, time series models. Experience with multiple programming languages, with a preference for SQL and Python. Familiarity with large language models and 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

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 ❯

analysis in a commercial environment A good understanding of statistical topics and the ability to explain them to non-technical stakeholders. For example, this would include hypothesis testing and linear regression Experience planning and completing analytical tasks on time, being responsible for gathering and defining analysis requirements, and having the courage to challenge misconceptions Confidence analysing data with More ❯

Azure Machine Learning Integrated with Power BI Get familiar with Machine Learning Workspace Predict Diabetes Score using Linear Regression Prerequisites- Requires Azure Subscription for creating Automated ML Workspace Install Python on your system Understanding of Linear Regression algorithm Let’s first have a quick overview on Linear Regression and then we will deep dive … into the process of creating Automated ML model and this model will get integrated into Power BI. Linear regression is a linear approximation of a relationship between two or more variables. Regressor model are highly used by data scientist to make prediction over continuous numerical values. Basically, the process of linear regression is mentioned as … as per your choice but it should follow some objective of making predictions Design Machine Learning Model that works on the dataset Make predictions on the dataset (based on Linear regression algorithm There is dependent variable which is called Y being predicted and independent variable X1, X2, X3..........Xn . Here x is a predictor and Y is function 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 ❯

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 … Experience and Skills: Data Science: Proficient in programming languages like Python, R, and SQL including data manipulation, data imputation, statistical modelling, and visualisation libraries. 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 ❯

team fully remotely! The successful candidate will manage a team of 4 Data Scientists, providing technical guidance and mentorship. The role involves building models for KPI trackers, primarily using linear regression and time series analysis. Additionally, there may be integration tasks between different software systems, so knowledge of software development tools is a plus. Required Experience Web Scraping … Statistical Modelling - Regression, time series, clustering Proficiency in Python & SQL Preferred Skills and Experience Experience with Pandas, Kubernetes, TensorFlow, Docker Strong knowledge in statistics and data analysis #J-18808-Ljbffr More ❯

a centralised team, collaborating with Data Scientists, Python developers, Actuaries and senior insurance experts to drive innovation in pricing and risk assessment by developing GLM, Gradient Boost, Bayesian and Linear Regression models for pricing models. What You’ll Be Doing: Enhancing actuarial models with advanced statistical and machine learning techniques. Developing and optimising pricing models using R, tidyverse More ❯

data using SQL (Google BigQuery) and Python. Strong foundational knowledge with practical experience in designing and analyzing A/B tests. Well-versed in various analysis techniques, such as linear and logistic regression, significance testing, and statistical modeling. Previous experience in the IAM domain is a strong plus but not a must. This is an excellent opportunity to More ❯

end-to-end modelling projects and collaborating closely with Data Viz, Planning and Client Services. You’ll: Lead high-impact analytics projects from brief to delivery Apply modelling techniques (linear regression, incrementality etc.) to solve real business problems Build trusted relationships with client teams and external stakeholders Present findings with confidence and strategic insight Mentor junior analysts and … shape delivery processes Balance multiple workstreams and manage timelines with ease What you’ll need to bring Experience in media/advertising analytics (MMM, regression modelling, incrementality, etc.) Fluency in one or more of Python, R, SQL, Alteryx, Snowflake, Tableau A proactive, solutions-focused mindset Strong communication skills – both with numbers and narratives Commercial acumen and a deep understanding 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 ❯

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. … to Mohammed Buhariwala at Harnham using the Apply link on this page or connect directly to find out more. Keywords Insight Analyst, Customer Analytics, Data Science, SQL, Python, Forecasting, Linear Regression, Marketing Analytics, Churn, Segmentation, Experimentation, A/B Testing, Membership, Subscription, Data Modelling, Hybrid, Remote. 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 ❯

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 ❯