ZipRecruiter

Log In

1

Python Data Scientist Jobs in Irvine, CA (NOW HIRING)

previous pagenext page

Showing results 21-40

All JobsPython Data Scientist JobsPython Data Scientist Jobs in Irvine, CA

Python Data Scientist information

See Irvine, CA salary details

$40.3K

$131.7K

$210.9K

How much do python data scientist jobs pay per year?

As of Sep 7, 2026, the average yearly pay for python data scientist in Irvine, CA is $131,746.00, according to ZipRecruiter salary data. Most workers in this role earn between $105,700.00 and $146,000.00 per year, depending on experience, location, and employer.

What is a Python data scientist?

A Python Data Scientist is a professional who uses Python programming language and its data analysis libraries to extract insights from large datasets. They apply statistical techniques, machine learning algorithms, and data visualization tools to solve business problems and make data-driven decisions. Python Data Scientists often work with tools like pandas, NumPy, scikit-learn, and Jupyter notebooks to manipulate data and build predictive models. Their role typically involves collecting, cleaning, analyzing, and interpreting complex data to help organizations make informed decisions.

What are some common challenges faced by Python data scientists when working with large datasets?

Python Data Scientists often encounter challenges related to processing and analyzing large datasets, such as memory limitations and slow computation times. To address these, professionals typically use libraries like Pandas, Dask, or PySpark to optimize data handling and leverage parallel computing. Collaborating closely with data engineers and IT teams can also help in setting up efficient data pipelines and scalable infrastructure. Staying updated with best practices in data preprocessing and model optimization is crucial for managing these challenges effectively.

What are the key skills and qualifications needed to thrive as a Python data scientist, and why are they important?

To thrive as a Python Data Scientist, you need strong analytical skills, a solid understanding of statistics, machine learning, and proficiency in Python programming, typically backed by a degree in computer science or a related field. Familiarity with tools and libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, and version control systems like Git is essential. Problem-solving, curiosity, and effective communication are standout soft skills for this role. These abilities are crucial for extracting actionable insights from data, building predictive models, and collaborating across multidisciplinary teams.

What is the difference between Python Data Scientist vs Data Analyst?

AspectPython Data ScientistData Analyst
Required SkillsPython, machine learning, statistical analysis, data modelingExcel, SQL, basic statistics, data visualization
CertificationsData Science certifications, Python programming coursesData analysis or business intelligence certifications
Work EnvironmentData science teams, R&D, predictive modeling projectsBusiness units, reporting, data visualization tasks
Industry UsageTech, finance, healthcare, e-commerceRetail, marketing, finance, healthcare

Python Data Scientists focus on building predictive models and advanced analytics using Python, while Data Analysts primarily interpret data through visualization and reporting. Both roles require strong analytical skills, but Python Data Scientists typically have more programming and machine learning expertise, making them suitable for complex data projects.

How much do Python data scientists make?

Python data scientists typically earn between $80,000 and $130,000 annually, depending on experience, location, and industry. Senior roles or those with specialized skills in machine learning and big data can command higher salaries, often exceeding $150,000. Compensation may also include bonuses and stock options in some companies.

Is Python good for data science?

Python is widely used by data scientists due to its simplicity, extensive libraries like Pandas, NumPy, and scikit-learn, and strong community support. It enables efficient data analysis, modeling, and visualization, making it a preferred programming language in the data science field.

What are popular job titles related to Python Data Scientist jobs in Irvine, CA?

For Python Data Scientist jobs in Irvine, CA, the most frequently searched job titles are:

What job categories do people searching Python Data Scientist jobs in Irvine, CA look for?

The top searched job categories for Python Data Scientist jobs in Irvine, CA are:

What cities near Irvine, CA are hiring for Python Data Scientist jobs?

Cities near Irvine, CA with the most Python Data Scientist job openings:

Python Data Scientist jobs near you
Infographic showing various Python Data Scientist job openings in Irvine, CA as of August 2026, with employment types broken down into 1% As Needed, 84% Full Time, 12% Part Time, and 3% Contract. Highlights an 88% Physical, 3% Hybrid, and 9% Remote job distribution, with an average salary of $131,746 per year, or $63.3 per hour.

Manufacturing Data Scientist

Rieke Packaging Systems

City Of Industry, CA • On-site

Full-time

Re-posted 17 days ago

Job description

About PennAero:
PennAero is a leading manufacturer of highly engineered fasteners and specialized components for critical aerospace, defense, space, and advanced energy applications. We partner with customers to solve their most complex challenges, bringing technical depth and disciplined, agile execution when it matters most. Experience guides our growth-strengthening capabilities and expanding our global platform as markets evolve. To learn more about PennAero's capabilities and commitment to aerospace excellence, visit https://pennaero.com

Position Overview
We are seeking a Manufacturing Data Scientist to transformcomplex operational data into actionable insights that improve productivity,quality, cost, reliability, and supply-chain performance. This role willpartner with manufacturing, engineering, quality, supply chain, finance, andinformation technology teams to develop analytical solutions that supportdata-driven decision-making across the organization.
The ideal candidate has strong expertise in Python and SQL,experience working with enterprise resource planning systems, and a practicalunderstanding of manufacturing processes and data. This individual must becomfortable working with large, complex datasets and translating analyticalfindings into clear recommendations for technical and nontechnicalstakeholders.
Key Responsibilities
Analyze manufacturing, production, quality, maintenance, inventory, and supply-chain data to identify trends, risks, inefficiencies, and improvement opportunities.
Build, validate, and maintain data pipelines and reusable analytical datasets using SQL and / or Python
Develop predictive and prescriptive models for applications such as equipment reliability, predictive maintenance, quality forecasting, yield optimization, demand planning, inventory optimization, and production scheduling.
Extract, clean, reconcile, and integrate data from ERP systems, MES, quality systems, equipment sensors, HCM systems, and other operational sources
Partner with manufacturing engineers, plant leaders, quality teams, supply-chain professionals, and business stakeholders to define analytical requirements and measurable success criteria.
Create dashboards, reports, and data visualizations that communicate operational performance and model results clearly.
Conduct root-cause analyses related to production losses, downtime, scrap, rework, throughput, cycle time, and process variation.
Develop and monitor key performance indicators, including overall equipment effectiveness (OEE), first-pass yield, schedule attainment, capacity utilization, downtime, scrap rate, and inventory accuracy.
Deploy analytical models and establish processes for monitoring model performance, data quality, and business impact.
Document data sources, methodologies, assumptions, model limitations, and technical processes.
Promote data literacy and analytical best practices across manufacturing and operations teams.
Ensure analytical solutions comply with applicable data governance, security, quality, and regulatory requirements.

Apply