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Entry Level Python Data Science Jobs in Austin, TX

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 ...

Apple

Data Scientist

Austin, TX · On-site

Act as the technical lead for data science projects focused on improving internal IT support ... Using Python to perform data wrangling, cleaning, manipulation, data modeling, exploratory data ...

Apple

Data Scientist

Austin, TX

Act as the technical lead for data science projects focused on improving internal IT support ... Using Python to perform data wrangling, cleaning, manipulation, data modeling, exploratory data ...

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 ...

Apple

Senior Data Scientist, Apple Ads

Austin, TX · On-site

Minimum Qualifications Bachelor's degree in Statistics, Economics, Mathematics, Computer Science ... Python programming skills and experience with common analytical libraries, including an ...

INTERA Careers

Groundwater Modeler

Austin, TX · On-site

The ideal candidate will have strong Python programming skills and an interest in using data science, automation, and advanced analytical methods to improve groundwater modeling workflows and ...

Saxon Global

Data Scientist

Austin, TX

... Spark(Python or Scala), Hadoop and Hive primarily - Should have ability to build and manipulate ... Science field and related field Additional Information All your information will be kept ...

INTERA Incorporated

Groundwater Modeler

Austin, TX

The ideal candidate will have strong Python programming skills and an interest in using data science, automation, and advanced analytical methods to improve groundwater modeling workflows and ...

Incedo

Data Analyst

Austin, TX · On-site

Company Overview Incedo is a US-based consulting, data science and technology services firm with ... Python or R. You will be responsible for ensuring that data analysis is accurate, efficient, and ...

Incedo

Data Analyst

Austin, TX · On-site

Company Overview Incedo is a US-based consulting, data science and technology services firm with ... Python or R. You will be responsible for ensuring that data analysis is accurate, efficient, and ...

Central Health

Data Analyst

Austin, TX · On-site

... scientists to serve as a key resource for business intelligence, performance, clinical and ... Responsibilities-Develop and maintain complex SQL and/ or Python queries to retrieve, join, and ...

Central Health

Data Analyst

Austin, TX

... scientists to serve as a key resource for business intelligence, performance, clinical and ... Responsibilities-Develop and maintain complex SQL and/ or Python queries to retrieve, join, and ...

Central Health

Data Analyst

Austin, TX · On-site +1

... scientists to serve as a key resource for business intelligence, performance, clinical and ... Responsibilities -Develop and maintain complex SQL and/ or Python queries to retrieve, join, and ...

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Entry Level Python Data Science information

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How much do entry level python data science jobs pay per hour?

As of Jul 10, 2026, the average hourly pay for entry level 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 some common challenges faced by entry-level Python data scientists when starting out, and how can they be addressed?

Entry-level Python data scientists often encounter challenges such as managing large datasets, understanding the nuances of real-world data (like missing or inconsistent values), and effectively communicating technical findings to non-technical stakeholders. To address these challenges, it's helpful to develop strong data cleaning skills, practice using libraries like pandas and scikit-learn, and focus on improving data visualization and storytelling abilities. Additionally, seeking feedback from more experienced team members and participating in collaborative projects can accelerate learning and help overcome early hurdles.

What is an entry level Python data scientist?

An entry level Python data scientist is a professional who uses Python programming language to analyze, interpret, and visualize data, typically in the early stages of their data science career. They are responsible for collecting, cleaning, and preparing data, performing basic statistical analyses, and building simple machine learning models under supervision. These roles often require proficiency in Python libraries like pandas, NumPy, and scikit-learn, as well as good problem-solving skills. Entry level data scientists may work in industries such as finance, healthcare, marketing, or technology to help organizations make data-driven decisions.

What are the key skills and qualifications needed to thrive as an Entry Level Python Data Scientist, and why are they important?

To thrive as an Entry Level Python Data Scientist, you need a strong understanding of statistics, data analysis, and proficiency in Python programming, typically supported by a relevant degree or coursework. Familiarity with data science libraries (such as pandas, NumPy, and scikit-learn), data visualization tools, and basic SQL is commonly required. Analytical thinking, problem-solving, and effective communication help you interpret data and present findings clearly. These skills ensure you can extract meaningful insights from data, collaborate effectively, and contribute to data-driven decision-making.

What is the difference between Entry Level Python Data Science vs Entry Level Data Analyst?

AspectEntry Level Python Data ScienceEntry Level Data Analyst
Required SkillsPython, SQL, statistics, machine learning basicsExcel, SQL, data visualization, basic statistics
CertificationsPython programming, data science fundamentalsExcel certifications, basic data analysis courses
Work EnvironmentTech companies, startups, data-driven teamsBusiness departments, marketing, finance teams
Common UsageBuilding models, data cleaning, predictive analyticsReporting, data visualization, trend analysis

Entry Level Python Data Science roles focus on programming, machine learning, and predictive modeling, often requiring Python and statistical knowledge. Entry Level Data Analyst positions emphasize data reporting, visualization, and basic analysis using tools like Excel and SQL. Both roles are common in various industries, but Python Data Science roles typically involve more technical and coding skills, while Data Analyst roles focus on interpreting data for business insights.

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 Entry Level Python Data Science jobs in Austin, TX? For Entry Level Python Data Science jobs in Austin, TX, the most frequently searched job titles are:
What job categories do people searching Entry Level Python Data Science jobs in Austin, TX look for? The top searched job categories for Entry Level Python Data Science jobs in Austin, TX are:
What cities near Austin, TX are hiring for Entry Level Python Data Science jobs? Cities near Austin, TX with the most Entry Level Python Data Science job openings:
Entry Level Python Data Science jobs near you
Junior Data Scientist

Junior Data Scientist

Cushman & Wakefield

Austin, TX • On-site

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 16 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 158 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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