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Head Data Science Jobs in Texas (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 is a practitioner who thinks first like an economist, real estate analyst, or quantitative urban ...

Cushman & Wakefield

Junior Data Scientist

Austin, TX

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 ...

Cushman & Wakefield

Junior Data Scientist

Austin, TX

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 ...

Cushman & Wakefield

Junior Data Scientist

Austin, TX

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 ...

CharterUP

Data Analyst

Austin, TX · On-site +1

$70K - $75K/yr

Head of Business Intelligence, Finance and Accounting Location: Austin, TX. (Hybrid: Monday ... Mathematics, Applied Mathematics, Statistics, Quantitative Economics, Data Science, Quantitative ...

Invitation Homes

VP, Enterprise Data

Dallas, TX · On-site

Report to the Head of Technology and provide executive leadership over the Enterprise Data ... Build and maintain strong relationships with analytics, data science, and senior leaders across all ...

Invitation Homes Inc.

VP, Enterprise Data

Dallas, TX · On-site

$177.82 - $308.23/hr

Report to the Head of Technology and provide executive leadership over the Enterprise Data ... Build and maintain strong relationships with analytics, data science, and senior leaders across all ...

Invitation Homes, Inc.

VP, Enterprise Data

Dallas, TX · On-site

Report to the Head of Technology and provide executive leadership over the Enterprise Data ... Build and maintain strong relationships with analytics, data science, and senior leaders across all ...

Invitationhomes

VP, Enterprise Data

Dallas, TX

Report to the Head of Technology and provide executive leadership over the Enterprise Data ... Build andmaintainstrong relationships with analytics, data science, and senior leaders across all ...

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All JobsHead Data Science JobsHead Data Science Jobs in Texas

Head Data Science information

See Texas salary details

$19.8K

$96.8K

$179.4K

How much do head data science jobs pay per year?

As of Jul 26, 2026, the average yearly pay for head data science in Texas is $96,846.00, according to ZipRecruiter salary data. Most workers in this role earn between $52,766.00 and $131,035.00 per year, depending on experience, location, and employer.

How to become head of data science?

To become a head of data science, professionals typically need extensive experience in data analysis, machine learning, and leadership roles, often requiring 8-10 years in data-related positions. A strong educational background in computer science, statistics, or related fields, along with skills in programming, data management, and strategic planning, is essential. Advanced degrees and certifications in data science or analytics can also enhance prospects for leadership positions.

Is 40 too late for data science?

The Head Data Science role and similar data science positions do not have strict age limits; many professionals transition into data science later in their careers. Success depends on relevant skills, experience, and continuous learning in areas like programming, statistics, and machine learning, regardless of age.

What is the highest paid job in data science?

The highest paid roles in data science are often senior positions such as Chief Data Officer, Director of Data Science, or Lead Data Scientist, with salaries exceeding $150,000 annually and sometimes reaching over $200,000 for those with extensive experience, advanced skills in machine learning, and industry expertise. These roles typically require strong leadership, strategic thinking, and proficiency with tools like Python, R, and cloud platforms.

What is the 80 20 rule in data science?

In data science, the 80/20 rule, also known as Pareto principle, suggests that roughly 80% of results come from 20% of the efforts or features. Data scientists often use this concept to focus on the most impactful variables or tasks to optimize model performance and efficiency.

What does a Head of Data Science do?

A Head of Data Science is responsible for leading and managing the data science team within an organization. They oversee the development and implementation of data-driven strategies, ensuring that the team delivers valuable insights and predictive models to support business goals. This role involves collaborating with other departments, setting the vision for data initiatives, and ensuring best practices in data analysis and machine learning are followed. Additionally, the Head of Data Science often mentors team members and helps shape the organization's overall data strategy.

What are some common challenges faced by a Head of Data Science when building and leading a data science team?

As a Head of Data Science, one of the main challenges is balancing strategic leadership with hands-on technical guidance. You'll often need to align the team's goals with broader business objectives while ensuring that team members have the right mix of skills and resources. Additionally, fostering effective collaboration between data scientists, engineers, and business stakeholders can be complex, especially in cross-functional environments. Managing expectations around project timelines and communicating technical insights in a clear, actionable way are also key aspects of the role.

What are the key skills and qualifications needed to thrive as a Head of Data Science, and why are they important?

To thrive as a Head of Data Science, you need advanced expertise in statistics, machine learning, data modeling, and a strong background in computer science or a related quantitative field, often supported by a master's or Ph.D. Proficiency with programming languages like Python or R, big data platforms such as Hadoop or Spark, and familiarity with cloud-based analytics tools are typically required. Strategic leadership, excellent communication skills, and the ability to mentor and inspire teams are crucial soft skills for this role. These abilities are essential to drive data-driven decision-making, foster innovation, and align analytics initiatives with organizational goals.

What is the difference between Head Data Science vs Data Science Manager?

AspectHead Data ScienceData Science Manager
ResponsibilitiesStrategic leadership, setting data science vision, overseeing multiple teamsTeam management, project delivery, coordinating data science projects
Required SkillsAdvanced analytics, leadership, strategic planningTeam management, technical expertise, project management
ExperienceSenior data science background, leadership rolesData science experience with managerial responsibilities
Work EnvironmentExecutive level, cross-departmental collaborationTeam-focused, project-oriented

The Head Data Science typically holds a strategic, leadership role overseeing the entire data science function, while the Data Science Manager focuses on managing teams and project execution. Both roles require strong technical backgrounds, but the Head Data Science emphasizes vision and strategy, whereas the Data Science Manager concentrates on operational management.

What are the most commonly searched types of Data Science jobs in Texas? The most popular types of Data Science jobs in Texas are:
Head Data Science jobs near you
Infographic showing various Head Data Science job openings in Texas as of July 2026, with employment types broken down into 1% As Needed, 84% Full Time, 11% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $96,846 per year, or $46.6 per hour.
Junior Data Scientist

Junior Data Scientist

Cushman & Wakefield

Austin, TX

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 2 days ago

Cushman & Wakefield rating

7.5

Company rating: 7.5 out of 10

Based on 154 frontline employees who took The Breakroom Quiz

103rd of 200 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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