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Python Data Science Jobs in Austin, TX (NOW HIRING)

Cushman & Wakefield

Junior Data Scientist

Austin, TX

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate ... Proficiencyin Python and/or R for data analysis, modeling, and pipeline construction; working ...

Cushman & Wakefield

Junior Data Scientist

Austin, TX

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate ... Proficiencyin Python and/or R for data analysis, modeling, and pipeline construction; working ...

Cushman & Wakefield

Junior Data Scientist

Austin, TX

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate ... Proficiencyin Python and/or R for data analysis, modeling, and pipeline construction; working ...

Cushman & Wakefield

Junior Data Scientist

Austin, TX · On-site

This position will report to the Head of Data Science and Geospatial Analytics. The ideal candidate ... Proficiencyin Python and/or R for data analysis, modeling, and pipeline construction; working ...

DoorDash

Analytics Engineer, Data Science

Austin, TX · On-site

Collaborate with data scientists, data engineers, and business stakeholders to understand business ... language such as Python or Scala * Experience in creating compelling reporting and data ...

Sustainment

Data Scientist

Austin, TX · On-site

Secret or Top Secret security clearance * 4+ years of experience in Data Science, Applied ML, Analytics, or a related data-focused role * Strong proficiency in Python and SQL * Demonstrated ...

CharterUP

Staff Data Scientist

Austin, TX · On-site

Establish the principles, infrastructure, and systems for data science, ensuring a scalable ... Advanced proficiency with SQL in big data environments, Python/R for large-scale analysis, and ...

Arrive Logistics

Data Scientist II

Austin, TX · On-site

... Science, Product, and Engineering teams to build and improve ML and AI systems that drive ... in Python and SQL, and comfort working with structured and unstructured data. • Ability to ...

Ouro

Lead Data Scientist

Austin, TX · On-site

Required : • Bachelor's degree in Data Science, Computer Science, Statistics, Mathematics, or a ... OR a PhD with 3 years of experience. • Expert-level proficiency in Python or R, and advanced SQL ...

Charles Schwab Inc.

Principal Data Scientist

Austin, TX · On-site

$215K - $235K/yr

Organization / Role Description In this role, you will be part of the Schwab AI & Data Science ... experience using Python and SQL to develop production-grade, modular, and optimized code.

Deloitte

Agentic AI, AI & Data Science Engineer

Austin, TX · On-site

$113K - $136K/yr

Work you'll do As an AI and Data Science Engineer III on the AI & Data team, you will be ... using Python * 1+ years of direct experience developing agentic AI systems, including agent ...

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How much do python data science jobs pay per hour?

As of Jul 15, 2026, the average hourly pay for python data science in Austin, TX is $58.11, according to ZipRecruiter salary data. Most workers in this role earn between $47.88 and $66.01 per hour, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Python Data Science position, and why are they important?

To thrive in Python Data Science, you need strong programming skills in Python, a solid understanding of statistics, data manipulation, and experience with data analytics or machine learning, often supported by a bachelor’s or master’s degree in a quantitative field. Familiarity with tools such as pandas, NumPy, scikit-learn, Jupyter Notebooks, and knowledge of SQL are typically essential; certifications like Google Data Analytics or IBM Data Science can be advantageous. Critical thinking, problem-solving, and effective communication are key soft skills for translating data insights into actionable business recommendations. These skills are crucial to efficiently analyze large datasets, build predictive models, and deliver meaningful insights that drive decision-making.

How much does a Python data scientist make?

A Python data scientist's salary typically ranges from $80,000 to $130,000 annually, depending on experience, location, and industry. Professionals with strong skills in machine learning, statistical analysis, and data visualization tools like Pandas and TensorFlow tend to earn higher salaries.

What are typical day-to-day responsibilities in a Python Data Science role?

In a Python Data Science role, your typical day might involve collecting, cleaning, and preparing raw data, exploring datasets to uncover patterns and trends, and building or evaluating predictive models. You’ll regularly use Python libraries to conduct analyses, visualize results, and collaborate with cross-functional teams such as product managers or engineers to define business objectives. Presenting your findings in clear, actionable formats for both technical and non-technical stakeholders is also a key part of the job. This dynamic environment emphasizes continuous learning, problem-solving, and close communication with other departments to align analytical insights with organizational goals.

Is Python useful in data science?

Python is a fundamental tool for data scientists, including those in data science roles, due to its extensive libraries such as Pandas, NumPy, and scikit-learn that facilitate data analysis, visualization, and machine learning. Its simplicity and versatility make it a preferred programming language in the data science field, often complemented by knowledge of SQL and data visualization tools.

What is a Python Data Science job?

A Python Data Science job involves using Python to analyze, process, and visualize data to extract insights and inform decision-making. It typically includes working with libraries like Pandas, NumPy, and Scikit-learn for data manipulation, statistical analysis, and machine learning. Professionals in this role may clean and preprocess data, build models, and communicate findings through reports or visualizations. Python Data Scientists often work in industries like finance, healthcare, and technology to solve complex problems and optimize business strategies.

Is 40 too late for data science?

Age is not a barrier to becoming a data scientist; many professionals transition into data science at various ages. Success depends on acquiring relevant skills such as programming in Python, understanding statistics, and working with tools like Jupyter notebooks, regardless of age.

Is Python a high paying job?

Python Data Science roles are generally well-paid due to high demand for skills in data analysis, machine learning, and automation. Salaries vary based on experience, location, and industry, but professionals with Python expertise often earn above average wages in the tech sector.
What are the most commonly searched types of Python Data Science jobs in Austin, TX? The most popular types of Python Data Science jobs in Austin, TX are:
What are popular job titles related to Python Data Science jobs in Austin, TX? For Python Data Science jobs in Austin, TX, the most frequently searched job titles are:
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Python Data Science jobs near you
Junior Data Scientist

Junior Data Scientist

Cushman & Wakefield

Austin, TX

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 21 days ago

Cushman & Wakefield rating

7.5

Company rating: 7.5 out of 10

Based on 153 frontline employees who took The Breakroom Quiz

76th of 160 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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