6 Permanent Linear Regression Jobs

JavaScript. Database management skills, including hands-on experience with designing, implementing, and optimizing databases. Experience implementing machine learning algorithms and embedding techniques such as linear regression, logistic regression, Word2Vec, or other AI/ML frameworks. Proficiency in using orchestration tools such as Kubernetes, Docker, and Helm. Strong more »

JavaScript. Database management skills, including hands-on experience with designing, implementing, and optimizing databases. Experience implementing machine learning algorithms and embedding techniques such as linear regression, logistic regression, Word2Vec, or other AI/ML frameworks. Proficiency in using orchestration tools such as Kubernetes, Docker, and Helm. Strong more »

client-friendly manner. Experience: Experience in a similar role within a Media Agency environment, delivering MMM and attribution model projects. Proficiency in Bayesian and linear regression approaches; familiarity with other machine learning techniques is advantageous. Extensive experience in data mining and analysis, including designing methodologies to address ad more »

finance, funding, liquidity, capital etc. skills in structuring calculation frameworks (e.g. inputs, scenarios, mathematical logic, linkages and integrations). skills such as trend analysis, linear regression, migration matrices, and replicating finance business logic are a requisite. in programming languages and data structures such as SAS, SQL, Python, Excel more »

e-commerce testing and measurement strategies such as Geo-testing and marketing attribution. You are an expert in using various analysis techniques, such as linear and logistic regression, significance testing, and statistical modelling. Educated to degree level in a numerate/analytical subject. Solutions focused approach, with an more »

and SQL. Familiarity with data manipulation and analysis libraries (e.g., pandas, numpy, jupyter, scikit-learn). Knowledge of machine learning and statistical methods (e.g. linear/logistic regression, decision trees, random forest, unsupervised methods) is preferred. Ability to convey complex information through data visualisation. Ability to manage different more »