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Linear Regression Jobs (NOW HIRING)

Entry Level Data Scientiest

Los Angeles, CA · On-site

$18 - $24/hr

Machine Learning Algorithms - Linear Regression, Logistic Regression, Decision Tree * Unsupervised/Clustering algorithms * NLP models, Deep Learning models for image classification Desired Candidate ...

Entry Level Data Scientiest

Manchester, NH · On-site

$16.50 - $22.25/hr

... Linear Regression, Logistic Regression, Decision Tree Unsupervised/Clustering algorithms NLP models, Deep Learning models for image classification Desired Candidate Profile Skills required: Hands on ...

DS with GEN AI

Murphy, TX · On-site

$14.25 - $18.50/hr

... Linear Regression, Clustering, Decicion Tree, KNN, SVN, etc. • LangChain & LangGraph: Hands-on experience building, deploying, and maintaining applications using LangChain and LangGraph frameworks ...

DS with GEN AI

Plano, TX · On-site

$14.25 - $18.50/hr

... Linear Regression, Clustering, Decicion Tree, KNN, SVN, etc. • LangChain & LangGraph: Hands-on experience building, deploying, and maintaining applications using LangChain and LangGraph frameworks ...

... linear predictive (e.g. logistic) regression and machine learning Additional Information All your information will be kept confidential according to EEO guidelines.

Lead Forecasting Engineer

Toledo, OH · On-site

$100K - $132K/yr

Familiarity with basic statistics and regression algorithms (Experience with Microsoft Linear Regression in SQL Server is a plus) * Familiarity with C# and ASP.Net is a plus * Familiarity with ...

Apply statistical and mathematical techniques, including logistic and linear regression, to solve business problems. Perform data analysis, feature engineering, model training, testing, and ...

Showing results 21-40

Linear Regression information

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$11

$51

$69

How much do linear regression jobs pay per hour?

As of Aug 6, 2026, the average hourly pay for linear regression in the United States is $51.44, according to ZipRecruiter salary data. Most workers in this role earn between $42.55 and $59.38 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a data analyst specializing in linear regression?

To excel as a Data Analyst specializing in Linear Regression, you need a strong background in statistics, mathematics, and data interpretation, typically supported by a relevant degree in data science, mathematics, or a related field. Familiarity with statistical software and programming languages such as R, Python (with libraries like scikit-learn), and data visualization tools is essential. Critical thinking, problem-solving, and effective communication are vital soft skills for interpreting results and conveying insights to stakeholders. These competencies are crucial for accurately modeling relationships within data, making data-driven decisions, and providing actionable recommendations.

What is linear regression?

Linear regression is a statistical method used to model the relationship between a dependent variable and one or more independent variables by fitting a linear equation to the observed data. It aims to find the best-fitting straight line (in simple linear regression) that predicts the value of the dependent variable based on the values of the independent variables. Linear regression is widely used in data analysis, forecasting, and machine learning for tasks such as predicting trends and estimating relationships between variables. It is one of the simplest and most interpretable techniques in statistics and predictive modeling.

What are common challenges faced by professionals working with linear regression models in real-world data analysis?

One of the main challenges when applying linear regression in real-world scenarios is dealing with data that may not meet the assumptions of linearity, homoscedasticity, and normality of residuals. Additionally, real data often contains outliers or multicollinearity among predictors, which can skew results and reduce model reliability. Professionals typically spend significant time on data preprocessing, feature selection, and validating model performance. Collaboration with domain experts is crucial to ensure that chosen variables make sense and that model outputs are actionable for business or research decisions.

What is the difference between Linear Regression vs Data Analyst?

AspectLinear RegressionData Analyst
Primary RoleBuilds statistical models to predict outcomesAnalyzes data to identify trends and support decision-making
Skills RequiredStatistics, programming (Python/R), data modelingData visualization, Excel, SQL, basic statistics
Work EnvironmentData science teams, research projectsBusiness units, reporting, dashboards
CertificationsData Science, Machine Learning certificationsData Analysis, Business Intelligence certifications

While Linear Regression focuses on creating predictive models using statistical techniques, Data Analysts interpret data to generate insights and support business decisions. Both roles require analytical skills, but Linear Regression specialists often have a stronger background in statistics and programming, whereas Data Analysts focus on data visualization and reporting.

More about Linear Regression jobs
What states have the most Linear Regression jobs? States with the most job openings for Linear Regression jobs include:
Infographic showing various Linear Regression job openings in the United States as of August 2026, with employment types broken down into 75% Full Time, 8% Temporary, and 17% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $106,997 per year, or $51.4 per hour.

Entry Level Data Scientiest

SynergisticIT

Los Angeles, CA • On-site

$18 - $24/hr

Other

Re-posted 11 days ago


Job description

Job Title

Synergistic IT is a full-service staffing and placement firm servicing clients in America for the past 12+ years. We are dedicated towards fulfilling the IT needs of our clients. From staffing to full implementation of projects we provide the highest quality IT Services. We intend to deliver exceptional student outcome. We don't just help you secure a tech job but build a solid career in technology.

Job Description

Good understanding of the below models:

  • Identify valuable data sources and automate collection processes
  • Undertake preprocessing of structured and unstructured data
  • Analyze large amounts of information to client trends and patterns
  • Classifier, Random Forest Classifier, Nave Bayes, Support Vector Machine
  • Machine Learning Algorithms - Linear Regression, Logistic Regression, Decision Tree
  • Unsupervised/Clustering algorithms
  • NLP models, Deep Learning models for image classification
Desired Candidate Profile

Skills required:

  • Hands on experience Python scripting
  • Hands on experience in building Machine Learning and Artificial Intelligence models
  • Good knowledge on Exploratory Data Analysis (EDA)
  • Hands on experience on platforms - Microsoft Azure/Amazon Web Services
  • Libraries – Numpy, Pands, Scikit learn, Seaborn, Plotly, TensorFLow, Should be able to do data visualisation using Tableau or Excel.
  • Excellent English communication (both oral and written) and reading comprehension skills.
  • Strong analytical and problem-solving skills, with clear attention to detail.

Education Requirement:

Bachelors, Masters in Computer Science/ Computer Engineering/ Information Systems/Information Technology/ Electrical Engineering/ Mechanical Engineering.

Benefits:

  • On Job Technical support
  • E- verified
  • Filing of H1b and Green card
  • Full time position

Candidate who are missing the required skills, might be provided an option to enhance their skills, so that they can also apply for the role and can make a career in IT industry. If you do respond via e-mail, please include a daytime phone number so that we can reach you. In considering candidates, time is of the essence, so please respond ASAP. Thank you