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Data Taxonomy Jobs in Austin, TX (NOW HIRING)

Senior Advisor, Data Science Data Science Senior Advisor (Taxonomy, Ontology, and Governance) Data Science is all about breaking new ground to enable businesses to answer their most urgent questions.

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Senior Advisor, Data Science

Hopkinton, MA

$150K - $150K/yr

Senior Advisor, Data Science Data Science Senior Advisor (Taxonomy, Ontology, and Governance) Data Science is all about breaking new ground to enable businesses to answer their most urgent questions.

Senior Advisor, Data Science

Round Rock, TX · On-site

$127K - $127K/yr

Senior Advisor, Data Science Data Science Senior Advisor (Taxonomy, Ontology, and Governance) Data Science is all about breaking new ground to enable businesses to answer their most urgent questions.

Data Architect / Engineer

Austin, TX · On-site

$140 - $190/hr

You will define the schema, taxonomy and graph model for our knowledge domains, build resilient ... Deep data modeling across relational and graph paradigms; graph databases (Neo4j) and Postgres ...

The successful candidate will apply expertise in benthic ecology, taxonomy, habitat characterization, and biological data analysis to support ocean exploration missions, scientific reporting, and ...

Programmatic Specialist

Austin, TX · Remote

$65K - $80K/yr

Evaluate DSPs, data partners, betas, and new ad formats, and recommend what earns a place in our stack. * Apply QA, taxonomy, and naming standards consistently, and help document how we do this to ...

... taxonomy, product presentation, storytelling, and promotional strategies drive both brand ... Balance data-driven decisions with strong creative, retail, and product instincts. Trend & Market ...

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Data Taxonomy information

What are some typical challenges faced when developing and maintaining a data taxonomy within an organization?

One common challenge when working in data taxonomy is ensuring consistency across different departments that may use varied terminology or classification standards. Data taxonomists often need to facilitate collaboration between stakeholders to agree on definitions and structures, which requires strong communication and negotiation skills. Another challenge is keeping the taxonomy up-to-date as business needs and data sources evolve, necessitating regular reviews and updates. Successfully navigating these issues helps improve data discoverability, governance, and overall business intelligence.

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

To thrive as a Data Taxonomist, you need a strong background in information science, data organization, and metadata management, often supported by a degree in library science, information systems, or a related field. Familiarity with taxonomy management tools, data modeling software, and standards such as SKOS or RDF is commonly required. Attention to detail, analytical thinking, and effective communication are essential soft skills for collaborating across teams and ensuring data consistency. These skills and qualifications are crucial for creating structured data frameworks that improve data discoverability, usability, and governance.

What is the difference between Data Taxonomy vs Data Analyst?

AspectData TaxonomyData Analyst
Primary FocusOrganizing and classifying data structuresAnalyzing data to extract insights
Skills & CertificationsData modeling, taxonomy development, data management certificationsStatistical analysis, SQL, data visualization skills
Work EnvironmentData management teams, data governance departmentsBusiness units, analytics teams
Industry UsageData governance, information architectureBusiness intelligence, reporting

Data Taxonomy involves creating structured classifications for data assets, ensuring consistency and clarity across systems. Data Analysts focus on interpreting data to support decision-making. While both roles work with data, Data Taxonomy emphasizes data organization, whereas Data Analysts analyze data for insights.

How to become a data taxonomist?

To become a data taxonomist, develop skills in data management, classification, and metadata standards, often through a degree in information science, computer science, or related fields. Gaining experience with data modeling tools, taxonomy development, and understanding domain-specific knowledge is essential, along with familiarity with data governance and relevant software such as Protégé or Excel.

What does a data taxonomy specialist do?

A data taxonomy specialist develops and maintains structured classifications of data within an organization to improve data organization, searchability, and governance. They analyze data assets, create standardized naming conventions, and often use tools like metadata management systems to ensure consistent data categorization across systems.

What skills are needed for data taxonomy?

Data taxonomy professionals need strong analytical skills to categorize and organize data effectively, along with knowledge of data management principles and metadata standards. Familiarity with data modeling tools, taxonomy development, and understanding of business context are also important. Proficiency in tools like Excel, SQL, or specialized taxonomy software can enhance performance.

What are popular job titles related to Data Taxonomy jobs in Austin, TX?

For Data Taxonomy jobs in Austin, TX, the most frequently searched job titles are:

What cities near Austin, TX are hiring for Data Taxonomy jobs?

Cities near Austin, TX with the most Data Taxonomy job openings:

Infographic showing various Data Taxonomy job openings in Austin, TX as of August 2026, with employment types broken down into 80% Full Time, and 20% Part Time. Highlights an 80% In-person, and 20% Remote job distribution.

Lead Product Manager, Partner Marketplace & Data Platforms

News Corporation

Austin, TX • On-site

$180 - $240/hr

Other

Posted 15 days ago


Job description

Recognized as the No. 1 site trusted by real estate professionals, Realtor.com® has been at the forefront of online real estate for over 25 years, connecting buyers, sellers, and renters with trusted insights and expert guidance to find their perfect home. Through its robust suite of tools, Realtor.com® not only makes a significant impact on the real estate industry at large, but for consumers, navigating the biggest purchase they will make in their life, by providing a user experience that is easy to use, easy to understand, and most of all, easy to make decisions.

Join us on our mission to empower more people to find their way home by breaking barriers to entry, making the right connections, and building confidence through expert guidance.

We're looking for a Lead Product Manager to build and scale a first‑of‑its‑kind partner platform and data ingestion ecosystem. This is a hands‑on leadership role, you'll own the strategy and get into the details, moving between executive alignment and sprint‑level execution depending on what the week calls for.

The core of the work is two‑sided: building a partner‑facing platform that drives real transaction volume, and engineering the backend infrastructure to capture, structure, and enrich high‑fidelity spatial and media assets at scale. The data flowing through this platform will feed AI model training and unlock new enterprise revenue streams. You'll be the connective tissue between executive vision, engineering reality, and the legal and financial guardrails that make it all defensible.

At this level, this role requires broad expertise across several disciplines: product, data engineering, commercial strategy, and cross‑functional leadership and the independent judgment to navigate significant ambiguity. You'll be accountable for outcomes that impact the broader organization, not just your immediate team.

What you’ll do: Roadmap Delivery & Execution

Own the product lifecycle and roadmap for our partner ecosystem and data pipeline. You'll translate business goals, specifically around data ownership and asset rights into a sequenced build plan that balances speed‑to‑market with long‑term defensibility. That means writing crisp PRDs, running sprint planning, and staying close enough to engineering to catch problems before they become blockers. You'll apply independent judgment in determining methods and sequencing, and your decisions will have real impact on the function.

API & Ingestion Engineering

Define the product requirements for our core ingestion channels: bulk upload APIs, automated system syncs, and batch pipelines. The goal is to replace fragmented, manual data handoffs with a clean, secure chain of custody for every asset that enters the platform. You'll also own the rights‑tagging infrastructure which is the layer that determines what's legally cleared for AI training and derivative content creation downstream, including emerging computer vision pipelines for next‑gen media offerings.

Data Taxonomy & Standardization

Work with Engineering and Data Science to establish a consistent metadata taxonomy including asset classification, attribute tagging, geolocation and make sure every asset flowing in is structured and rights‑cleared from the moment it arrives. This requires evaluating intangible factors and making judgment calls on taxonomy design that will shape how the entire platform scales, including how well it supports model training pipelines as our AI capabilities mature. Coverage of tagged, AI‑ready assets is a core platform KPI you'll own.

Algorithmic Mechanics & Ecosystem Incentives

Design the partner discovery and ranking logic so the platform naturally rewards higher‑quality, more valuable capture formats. Think carefully about the give‑get across partner horizons including what partners receive now versus what they unlock over time and make sure the mechanics actually produce the behavior you're after. This requires conceptual thinking about incentive structures and their second‑order effects on ecosystem health.

Commercialization & Cross‑Functional Operations

Work closely with Legal to make sure vendor onboarding and contract terms translate directly into platform guardrails including exclusivity structures, data transfer rights, retention clauses, and succession terms all need to live somewhere in the product, not just in a filing cabinet. With Finance and Ops, help scale the payment architecture and commercial pipelines. You'll coordinate across multiple groups and regularly persuade senior, non‑technical stakeholders on complex matters. As the asset library matures, support in building the infrastructure needed for enterprise licensing and potential M&A..

Enterprise Monetization Enablement

As the data library grows, build the scaffolding to aggregate, structure, and package it for high‑margin enterprise use cases for financial institutions, risk underwriting, institutional analytics, and advanced computer vision applications for next‑generation media products. This role focuses on platform readiness, not sales/partnership execution. Your job is to make sure the infrastructure can support those conversations when the business is ready to have them.

What you’ll bring:
  • 10+ years of related experience with a Bachelor's degree; 8+ years with a Master's degree; or a PhD with 5+ years in product management, with a track record delivering complex B2B/B2C marketplaces, API platforms, or enterprise data ingestion systems from early build through scale.

  • Broad expertise across several related disciplines including product strategy, data engineering, commercial operations, and legal/compliance frameworks. Able to lead across these areas without needing a hand‑off at every boundary.

  • Strong technical fluency. You're comfortable in the weeds with data pipelines, API design, and metadata schemas.

  • Proven ability to evaluate complex situations where the right answer isn't obvious, including commercial contracts, partner dynamics, and build vs. buy decisions, and exercise independent judgment to chart a course.

  • A clear, persuasive communicator who can adapt their style across technical teams, legal counsel, finance leadership, and C‑suite audiences often in the same week.

Strongly Preferred
  • Direct experience with machine learning workflows, computer vision, or 3D/spatial data, especially around model training pipelines or large‑scale media/image processing for AI applications.

  • A formal network builder. You've created lasting cross‑functional working relationships, not just one‑off alignments, and you're recognized internally as a subject matter expert others turn to.

  • Background in prop‑tech, real estate technology, digital media licensing, or two‑sided marketplace infrastructure.

What the First Year Looks Like

These milestones reflect a trajectory, not a rigid checklist. The expectation is that someone strong moves through the role roughly like this:

Early on, you're in listening and learning mode getting deep with Engineering, Legal, and our initial partners to understand what's actually true versus what's assumed. By the end of Q1 or earlier, you've got a clear‑eyed PRD, user stories, and an API schema blueprint that reflects reality, and you've synthesized early demand signals from an initial validation test to sharpen the core build plan.

By mid‑year, the alpha platform is live. Initial partners are ingesting through direct pipelines rather than manual handoffs, and assets are flowing in tagged, structured, and rights‑cleared. It won't be perfect, but it works and you know exactly what to fix next.

Into the back half, you're tuning the ecosystem. Ranking and incentive mechanics are live, and you can see partner behavior starting to shift toward higher‑quality, higher‑fidelity formats. You're iterating on what the data tells you, not just instinct, and adoption of premium capture options is measurably growing across the partner network.

By end of year, metadata mapping is largely automated and the asset library is structured enough that AI and enterprise teams can actually start using it. The platform has moved from a build project to a running business and the foundation is in place for downstream licensing and model training.

Do the best work of your life at Realtor.com®

Here, you’ll partner with a diverse team of experts as you use leading‑edge tech to empower everyone to meet a crucial goal: finding their way home. And you’ll find your way home too. At Realtor.com®, you’ll bring your full self to work as you innovate with speed, serve our consumers, and champion your teammates. In return, we’ll provide you with a warm, welcoming, and inclusive culture; intellectual challenges; and the development opportunities you need to grow.

Diversity is important to us, therefore, Realtor.com® is an Equal Opportunity Employer regardless of age, color, national origin, race, religion, creed, gender, sex, sexual orientation, gender identity and/or expression, marital status, status as a disabled veteran and/or veteran of the Vietnam Era or any other characteristic protected by federal, state or local law. In addition, Realtor.com® will provide reasonable accommodations for otherwise qualified disabled individuals.

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