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

REVOLVE

Senior Data Scientist

Cerritos, CA · On-site

$120K - $150K/yr

Main purpose of the Senior Data Scientist role: Use a diverse skill sets across math and computer ... Proficient in Python, NumPy and other packages * Familiar with statistical and ML methodology ...

Prodapt

Senior Data Scientist

Irvine, CA · On-site

We are seeking a highly skilled Data Scientist with expertise in demand forecasting, supply chain ... Hands-on experience with Python and relevant libraries: pandas, numpy, scikit-learn, statsmodels ...

iHerb, LLC

Pricing Data Scientist

Irvine, CA · On-site +1

The Pricing Data Scientist is a hands-on, high-autonomy individual contributor responsible for ... Independently develop analytical workflows using SQL and Python, moving fluidly between data ...

iHerb, LLC

Pricing Data Scientist

Irvine, CA · On-site +1

The Pricing Data Scientist is a hands-on, high-autonomy individual contributor responsible for ... Independently develop analytical workflows using SQL and Python, moving fluidly between data ...

iHerb.com

Pricing Data Scientist

Irvine, CA · On-site +1

The Pricing Data Scientist is a hands-on, high-autonomy individual contributor responsible for ... Independently develop analytical workflows using SQL and Python, moving fluidly between data ...

VSolvit

DATA SCIENTIST II

Norco, CA · On-site

$115K - $130K/yr

Data Scientist II On Site: Norco, CA Job Summary We are seeking a talented and driven mid-level ... Proficiency in Python, R, or similar programming languages for data analysis * Working knowledge in ...

omega solutions, Inc.

Sr. Data Scientist

Santa Ana, CA · On-site

Sr. Data Scientist Santa Ana, CA 6 months : What is the specific title of the position? Senior Data ... SQL, Python, Spark, Hive Libraries: Scikit-Learn, Numpy Analytics: Regression, Classification ...

Bio-Rad Laboratories

Data Scientist II

Irvine, CA · On-site

$121K - $166K/yr

Strong experience using Python for data analysis and machine learning. * Strong communication ... science and healthcare. As one of the top five life science companies, we are a global leader in ...

Bio-rad Laboratories, Inc.

Data Scientist II

Irvine, CA · On-site

$121K - $166K/yr

Strong experience using Python for data analysis and machine learning. * Strong communication ... science and healthcare. As one of the top five life science companies, we are a global leader in ...

Edwards Lifesciences

Senior Data Scientist

Irvine, CA · On-site

$108 - $153/hr

As a Senior Data Scientist, you own modeling for a clinical or product domain, drive problem ... Strong Python and SQL, and depth in modeling and experiment tracking such as PyTorch, TensorFlow ...

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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 Aug 8, 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.

How much does a Python Data Scientist make?

A Python Data Scientist's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually in the United States. Senior roles or those with advanced skills in machine learning and big data tools can earn higher compensation. Certifications and a strong portfolio can also influence salary levels.

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.

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 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 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.

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, 82% Full Time, 13% Part Time, and 4% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $131,746 per year, or $63.3 per hour.

Junior Data Scientist

Cushman & Wakefield

Costa Mesa, CA • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

This job post has expired today. Applications are no longer accepted.

Cushman & Wakefield rating

7.4

Company rating: 7.4 out of 10

Based on 158 frontline employees who took The Breakroom Quiz

109th of 201 rated real estate companies

Job description

Job Title

Junior Data Scientist

Job Description Summary

This role sits at the intersection of real estate economics, urban analysis, and data science. The Junior Data Scientist will support the development and evolution of Cushman and Wakefield Quantitative Insight Group's (QIG) analytical capabilities by producing rigorous, insight-driven work on commercial real estate markets across the Americas. This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban planner, and who brings the technical skills to build and operate the data infrastructure their own work requires.
This is not primarily an engineering role, though the ideal candidate will possess data engineering knowledge, skills, and abilities. The Analyst will spend most of their time doing substantive analytical and research work: synthesizing complex datasets, identifying market patterns and anomalies, and producing outputs that inform Cushman & Wakefield's House View, including elements that are unique to QIG, and related analytical products for key clients. At the same time, the candidate should be comfortable constructing and maintaining data pipelines, working fluently in Python and/or R and SQL, and collaborating closely with Technology & Data Solutions (TDS) as a knowledgeable and credible partner.

Job Description

Key Responsibilities

Real Estate & Urban Economic Analysis (45%)

  • Conduct rigorous quantitative analysis on commercial real estate markets, synthesizing property, macroeconomic, and urban data to surface market trends, structural shifts, and investment-relevant insights.

  • Apply econometric and statistical methods (time series modeling, regression, spatial econometrics, or similar) to real estate and labor market questions in support of QIG research products.

  • Integrate geospatial data and methods into analytical workflows: working with Census geographies, parcel data, land use classifications, walkability or transit metrics, demographic overlays, and similar inputs to enrich market analysis.

  • Contribute to the development of novel datasets and indicators that advance QIG's analytical edge, including working closely with the Head of Data Science & Geospatial Analytics to specify and build integrated data products combining proprietary CRE data with public and third-party sources.

  • Support the QIG team on ad hoc analytical requests from Americas Research, the Global Think Tank, and senior stakeholders, producing clean, well-documented, and reproducible outputs.

Data Engineering & Pipeline Maintenance (35%)

  • Build andmaintainautomated data pipelines for ingesting, transforming, and storing CRE and macroeconomic datasets used in analytical modelsand reoccurring analysis.

  • Ensure data integrity and consistency across QIG inputs and outputs through validation, quality control procedures, and structured data interfaces.

  • Perform exploratory data analysis and profiling on raw and processed datasets tovalidatepipeline outputs andidentifyanomalies or inconsistencies.

  • Partner with PRI (Property Research & Intelligence), TDS (Technology & Data Solutions), and the GIS team to ensure governance of time series and geospatial data, particularly as geography-based competitive sets evolve.

  • Serve as a knowledgeable liaison to TDS: translating analytical requirements into engineering specifications, tracking the status of data requests in the TDS backlog, and validating outputs against analytical expectations.

Documentation, Integration & Infrastructure (20%)

  • Develop andmaintaininternal documentation covering data sources, model architecture, data flows, and diagnostic procedures, with attention to field-level lineage and traceability.

  • Serve as the team's subject matter expert on integration and processing of internal, third-party vendor, and public datasets (e.g., Census TIGER, IPUMS, LODES, NLCD, Overture Maps), and advise on cleaning, normalization, andappropriate analyticalapplications.

  • Monitor the evolution of third-party data products; assess their fit against QIG analytical requirements and produce intake specifications when new sources are approved for integration.

  • Support the adoption of emerging analytical technologies (including ML/AI methods and advanced data infrastructure patterns) through hands-on prototyping and coordination with TDS whereappropriate.

Qualifications

  • Bachelor's degree inEconomics,Data Science,Real Estate, Applied Economics, Geography,UrbanPlanningor anyclosely related field with quantitative emphasis.A master's degree ispreferredand adoctoral degree is a plus.

  • 2 to 6yearsof experience ina research, analytical, or data science role, preferably in a real estate, urban policy, planning, or economic research context.

  • Strong command of quantitative methods: regression,time series analysis,spatial econometrics, or comparable approaches applied to real estate or urban economic questions.

  • Working knowledge of geospatial data and methods: experience with GIS tools (ArcGIS, QGIS, or programmatic approaches via R or Python), familiarity with spatial data formats and concepts, and comfort integrating geographic context into analysis.

  • Proficiencyin Python and/or R for data analysis, modeling, and pipeline construction; working knowledge of SQL. Familiarity with cloud platforms (Azure, AWS) and version control is a plus.

  • Experience working with public datasets commonly used in urban and real estate research: Census products (ACS, TIGER, LODES), BLS, IPUMS, or similar.

  • Ability to produce clean, well-documented, reproducible analytical work and communicate findings clearly to both technical and non-technical audiences.

  • Comfortable operating in a cross-functional environment, working both independently and alongside engineering and research teams on iterative deliverables.

  • Genuine intellectual interest in urban economics, commercial real estate markets, and the spatial dimensions of economic activity.

  • Comfortability in communicating analysis, methods and related topics withrelated teams and immediate management.


Cushman & Wakefield also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health, vision, and dental insurance, flexible spending accounts, health savings accounts, retirement savings plans, life, and disability insurance programs, and paid and unpaid time away from work. In addition to a comprehensive benefits package, Cushman and Wakefield provide eligible employees with competitive pay, which may vary depending on eligibility factors such as geographic location, date of hire, total hours worked, job type, business line, and applicability of collective bargaining agreements.
The compensation that will be offered to the successful candidate will depend on factors such as whether the position is covered by a collective bargaining agreement, the geographic area in which the work will be performed, market pay rates in that area, and the candidate's experience and qualifications.
The company will not pay less than minimum wage for this role.
The compensation for the position is: $ 114,750.00 - $135,000.00Cushman & Wakefield is an Equal Opportunity employer to all protected groups, including protected veterans and individuals with disabilities. Discrimination of any type will not be tolerated.

In compliance with the Americans with Disabilities Act Amendments Act (ADAAA), if you have a disability and would like to request an accommodation in order to apply for a position at Cushman & Wakefield, please call the ADA line at 1-888-365-5406 or emailAccommodations@cushwake.com. Please refer to the job title and job location when you contact us.

INCO: "Cushman & Wakefield"

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