19 of 19 Linear Regression Jobs in the UK excluding London

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 ❯

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 ❯

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 ~30 people, they are scaling quickly, supported by recent funding and a strong growth pipeline. They specialise in predictive analytics, tracking KPIs for a wide range of companies and … role in developing and refining KPI prediction models, working with real-world data to create 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 enhance workflows. Collaborate with the revenue team to generate insightful reports. Support internal product development by … pipelines and analysis. What They're Looking For 1-2 years in data science or a related field, or a Master’s degree. Strong Python programming (essential), SQL, and linear regression/statistical modeling. Experience with web scraping, machine learning, or dashboarding is a plus. A background in finance or exposure to financial data is advantageous but not More ❯

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 ❯

Social network you want to login/join with: 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 ~30 people, they are scaling quickly, supported by recent funding and a strong growth pipeline. They specialise in predictive analytics … role in developing and refining KPI prediction models, working with real-world data to create 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 enhance workflows. Collaborate with the revenue team to generate insightful reports. Support internal product development by … pipelines and analysis. What They're Looking For 1-2 years in data science or a related field, or a Master’s degree. Strong Python programming (essential), SQL, and linear regression/statistical modeling. Experience with web scraping, machine learning, or dashboarding is a plus. A background in finance or exposure to financial data is advantageous but not 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 ❯

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 ❯

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 ❯

internal and external stakeholders to deliver data-driven solutions. Essential experience: Python. Git for version control. Classical statistics. Hypothesis testing (parametric and non-parametric). Survival analysis techniques (Cox regression, etc). Linear or logistics regression models. Exposure to small datasets, not just large (very important). Desirable experience: Familiarity with pharma/health/medical datasets. 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 ❯

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 ❯

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 ❯

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 ❯

Computer Science, Data Science, AI, or a related discipline. Strong numerical and statistical knowledge (e.g. Bayesian/frequentist methods, probability distributions). Solid understanding of machine learning algorithms (e.g. linear/logistic regression, random forests, neural networks, time series models). Experience with multiple programming languages — with Python and SQL preferred. Interest or familiarity with large language models 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 ❯

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 ❯