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Weekend Machine Learning Jobs in Tempe, AZ (NOW HIRING)

Champions Funding LLC

Data Scientist

Gilbert, AZ · On-site

Description: * Design, develop, and evaluate machine learning, statistical, and predictive models to solve complex business challenges across multiple departments. * Apply modern artificial ...

Doist

Data Scientist

Chandler, AZ · On-site

$140 - $190/hr

Build and optimize machine learning models for classification, regression, predictive analytics, and time series forecasting. * Develop end‑to‑end ML pipelines and support deployment of models ...

Koantek

Data Scientist

Chandler, AZ · On-site

Build and optimize machine learning models for classification, regression, predictive analytics, and time series forecasting. * Develop end-to-end ML pipelines and support deployment of models into ...

Koantek

Data Scientist

Chandler, AZ · On-site

Build and optimize machine learning models for classification, regression, predictive analytics, and time series forecasting. Develop end-to-end ML pipelines and support deployment of models into ...

Unitek Learning

People Data Scientist

Tempe, AZ · On-site

This role leverages predictive modeling, experimentation, machine learning, and workforce analytics to identify trends, assess organizational effectiveness, and inform strategies related to talent ...

Unitek Learning

People Data Scientist

Tempe, AZ

This role leverages predictive modeling, experimentation, machine learning, and workforce analytics to identify trends, assess organizational effectiveness, and inform strategies related to talent ...

Unitek Learning

People Data Scientist

Tempe, AZ

This role leverages predictive modeling, experimentation, machine learning, and workforce analytics to identify trends, assess organizational effectiveness, and inform strategies related to talent ...

Dynalectric Company

Machine Operator

Mesa, AZ · On-site

$16.25 - $19.50/hr

Learning and Development * Cross-train on multiple machines and fabrication processes ... Overtime, including evenings or weekends, may be required to meet production deadlines. Some travel ...

Inherent Technologies

Data Scientist

Chandler, AZ · Remote

Key Responsibilities: - Design and implement advanced machine learning algorithms for time series forecasting. - Conduct exploratory data analysis using Python, SQL, and other tools. - Develop and ...

Dynalectric Company

Machine Operator

Mesa, AZ · On-site

$16.25 - $19.50/hr

Learning and Development * Crosstrain on multiple machines and fabrication processes. * Demonstrate ... Overtime, including evenings or weekends, may be required to meet production deadlines. Some travel ...

Pwc

AI Engineer

Phoenix, AZ · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

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Infographic showing various Weekend Machine Learning job openings in Tempe, AZ as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 22% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution.

Data Scientist

Champions Funding LLC

Gilbert, AZ • On-site

Full-time

Posted 24 days ago

Job description

Description:

• Design, develop, and evaluate machine learning, statistical, and predictive models to solve complex business challenges across multiple departments.
• Apply modern artificial intelligence and machine learning techniques, including large language models (LLMs), generative AI, and advanced analytics, to automate processes, enhance decision-making, and generate business insights.
• Translate business objectives into well-defined analytical, statistical, and machine learning solutions that deliver measurable business value.
• Analyze large, complex datasets to identify trends, patterns, opportunities, and operational improvements.
• Partner with data engineering, IT, and business teams to develop scalable data pipelines and deploy machine learning models into production environments.
• Evaluate data quality, model performance, and AI system limitations while ensuring responsible, ethical, and practical implementation of predictive models.
• Present analytical findings, recommendations, and technical concepts clearly to executive leadership and both technical and non-technical stakeholders.
• Develop, monitor, and optimize predictive models, ensuring ongoing performance, accuracy, and reliability through continuous improvement.
• Stay current with emerging technologies, AI advancements, machine learning methodologies, and data science best practices to identify opportunities for innovation.
• Collaborate across departments to support strategic initiatives, business intelligence projects, forecasting, automation, and operational optimization.
• Maintain thorough documentation of models, methodologies, assumptions, and development processes to support transparency, reproducibility, and governance.
• Support ad hoc analytical projects and provide data-driven recommendations that improve business performance and operational efficiency.

Requirements:

• Bachelor's degree required in Mathematics, Data Science, Computer Science, Engineering, Physics, or another quantitative discipline; advanced degree preferred.
• Strong technical foundation in statistics, predictive modeling, machine learning algorithms, and programming languages such as Python and SQL.
• Demonstrated experience working with modern AI technologies, including deep learning, large language models (LLMs), generative AI, MLOps, or related machine learning frameworks.
• Experience developing, deploying, and maintaining machine learning models in production environments.
• Strong understanding of cloud computing platforms and modern data science tools and technologies.
• Ability to evaluate model performance, balance trade-offs between accuracy, interpretability, speed, and risk, and apply sound judgment in ambiguous situations.
• Experience communicating complex technical concepts to business leaders and collaborating effectively with cross-functional teams.
• Experience within financial services, mortgage lending, or other highly regulated industries preferred.
• Familiarity with model governance, model risk management, compliance, or regulatory frameworks is a plus.