UX Data Researcher (Contract Position)

📍 Job Overview

Job Title: UX Data Researcher (Contract Position)

Company: HTX Labs

Location: Remote (United States)

Job Type: CONTRACTOR

Category: Operations - Data & Analytics / GTM Operations

Date Posted: November 26, 2025

Experience Level: 5-10 years

🚀 Role Summary

• This is a hybrid role blending deep UX research, data architecture, full-stack analytics engineering, and customer-embedded solution delivery, focusing on building and deploying XR-enabled capabilities.

• The position requires a strong foundation in data analytics, data architecture, and full-stack implementation to architect scalable data and analytics systems.

• Successful candidates will excel at synthesizing qualitative and quantitative insights into actionable product and UX recommendations for internal teams and external stakeholders.

• The role emphasizes rapid delivery of high-value solutions within customer environments, particularly within the DoD and enterprise training ecosystems, driving measurable outcomes through data-driven insights.

📝 Enhancement Note: The "UX Data Researcher" title, combined with responsibilities like "data architecture," "full-stack analytics engineering," and "customer-embedded solution delivery," points to a specialized role that bridges the gap between understanding user needs (UX Research) and building robust, data-driven systems (Data Engineering/Analytics). This isn't a typical GTM operations role but rather a specialized technical operations role with significant customer-facing responsibilities, often found in tech companies developing complex platforms. The "Forward Deployed" aspect suggests a hands-on, customer-centric approach to implementation and problem-solving.

📈 Primary Responsibilities

• Embed directly with customer teams (DoD, enterprise training) to thoroughly understand mission-critical problems, workflows, and success criteria for XR-enabled capabilities.

• Architect, build, and maintain scalable data and analytics systems designed to support XR training applications and user behavior tracking.

• Design and execute mixed-methods user research (usability testing, surveys, interviews, analytics) to uncover user behaviors, trends, and opportunities for product enhancement.

• Synthesize qualitative and quantitative data into actionable recommendations for Design, Product, and Engineering teams to influence product evolution and UX improvements.

• Own the technical delivery lifecycle from initial prototype development to stable production deployments, ensuring high-value, measurable outcomes for customers.

• Define Key Performance Indicators (KPIs), success metrics, and data collection strategies that align directly with product goals and customer objectives.

• Develop and maintain reusable tools, playbooks, and data frameworks to accelerate future deployments and standardize best practices across client engagements.

• Surface patterns and field insights gathered from customer interactions to directly influence the product and technology roadmap, ensuring continuous improvement.

• Collaborate closely with Product, Engineering, and Innovation & Design teams to ensure seamless integration and rapid iteration of XR-enabled solutions.

• Ensure data governance, security, and compliance are maintained across all built and managed data systems, adhering to relevant industry standards.

📝 Enhancement Note: The responsibilities clearly indicate a hands-on, technically proficient role that also requires strong customer-facing skills and strategic thinking. The emphasis on "customer-embedded delivery," "data architecture & analytics," and "UX & product insights" highlights the need for an individual who can bridge technical implementation with user-centric design and business outcomes, a hallmark of advanced operations roles in specialized tech sectors.

🎓 Skills & Qualifications

Education: While no specific degree is listed, a Bachelor's or Master's degree in Computer Science, Data Science, Human-Computer Interaction, Statistics, or a related quantitative field is typically expected for roles with this level of technical and analytical responsibility. Relevant certifications in data analytics, cloud platforms, or UX research may also be beneficial.

Experience: 5+ years in data engineering, data analytics, software engineering, or technical deployment roles, with a proven track record of delivering complex systems in fast-paced, ambiguous, or customer-facing environments.

Required Skills:

• Data Engineering & Architecture: Proficiency in database design, cloud-based architecture (AWS, Azure, GCP), and querying languages (SQL). Experience building and maintaining scalable data systems.

• Analytics & Data Visualization: Strong experience with data visualization tools (e.g., Tableau, Power BI, Looker), analytics platforms, and dashboarding techniques for clear communication of insights.

• UX Research & Synthesis: Demonstrated ability to turn research (usability testing, surveys, interviews) and data into clear, actionable insights and product/UX recommendations.

• Technical Execution: Ability to write or review production-grade code, particularly in Python and/or JavaScript, for system development and integration.

• Customer Engagement: Experience delivering complex technical solutions in fast-paced, ambiguous, or customer-facing environments, with strong communication and stakeholder management skills.

• Training Data Systems: Experience with Learning Record Stores (LRS), Learning Management Systems (LMS), SCORM, xAPI, or other training data systems.

• Agile Methodologies: Experience working within agile development processes to facilitate rapid iteration and delivery.

• Problem-Solving: A proactive problem-solver adept at creating clarity in ambiguous situations and sequencing delivery effectively.

• Authorization to Work: Must be authorized to work in the U.S.

Preferred Skills:

• XR/Spatial Computing: Experience with Extended Reality (XR), spatial computing, or immersive training technologies.

• AI/ML Integration: Experience deploying or integrating systems powered by Large Language Models (LLMs) or generative AI models.

• DoD/Enterprise Training Context: Familiarity with Department of Defense (DoD) environments, enterprise learning ecosystems, or complex customer delivery scenarios.

• Machine Learning & Predictive Analytics: Experience with machine learning techniques and predictive analytics for advanced data modeling.

📝 Enhancement Note: The required skills reflect a blend of technical data expertise and research capabilities, common in roles that drive product strategy through data. The specific mention of LRS, LMS, SCORM, and xAPI points to a niche within the learning and development technology sector, requiring specialized knowledge. The preference for XR and AI/ML experience aligns with HTX Labs' focus on advanced training technologies.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• Data System Design & Implementation: Showcase examples of data architectures you've designed and built, detailing the technologies used, scalability considerations, and data flow.

• Analytics & Dashboarding Projects: Present dashboards or reports created to track key metrics, highlighting your process for identifying KPIs, gathering data, and communicating insights effectively to stakeholders.

• UX Research & Insights Integration: Include case studies demonstrating how you've translated user research findings (qualitative or quantitative) into concrete product or system improvements, detailing the impact.

• Technical Delivery & Problem-Solving: Provide examples of complex technical projects delivered, emphasizing your approach to scope, sequence, and execution, especially in challenging or ambiguous environments. Include any custom tools or frameworks developed to streamline processes.

• Customer-Facing Solutions: If possible, include anonymized examples of solutions developed in collaboration with or for external customers, detailing the problem, your solution, and the measurable outcomes.

Process Documentation:

• Methodology Documentation: Demonstrate your ability to document data collection strategies, analytics pipelines, and research methodologies clearly and concisely.

• Workflow Optimization: Showcase instances where you've analyzed and improved existing data workflows or user processes for greater efficiency and effectiveness.

• System Implementation Plans: Present examples of how you've planned and executed the deployment of data systems or analytics solutions, including considerations for integration, security, and user adoption.

📝 Enhancement Note: For a role like this, a portfolio is crucial to demonstrate hands-on capabilities. The emphasis should be on showing the process behind the results – how data was analyzed, insights were derived, systems were engineered, and value was delivered. Case studies that highlight problem-solving in ambiguous or customer-facing scenarios are particularly valuable.

💵 Compensation & Benefits

Salary Range: As this is a contract position in the United States, the compensation will likely be structured as an hourly rate or a fixed project fee. Based on the experience level (5-10 years), the hybrid nature of the role (data engineering, UX research, analytics, client-facing), and the specialized domain (XR, DoD training), a competitive hourly rate would typically range from $70 to $120 per hour. This estimate is based on industry benchmarks for senior data engineers, analytics consultants, and UX researchers in remote US-based roles, adjusted for the advanced technical requirements and contract nature of the position.

Benefits: As a contractor, standard employee benefits may not apply. However, typical contractor benefits or considerations include:

• Competitive Hourly Rate: Reflecting the specialized skills and experience required.

• Flexible Work Schedule: Potential for flexible hours within the contract scope.

• Remote Work: Full remote work arrangement within the United States.

• Direct Impact: Opportunity to work on cutting-edge technology with significant customer impact.

• Networking: Exposure to clients in the DoD and enterprise training sectors.

Working Hours: The role is likely to require approximately 40 hours per week, typical for a full-time contract. However, specific project demands may necessitate flexibility, with the potential for occasional extended hours to meet critical deadlines or customer needs, especially during critical deployment phases.

📝 Enhancement Note: As a contract role, the salary is typically negotiated based on experience and market rates. The provided range is an estimate for senior-level technical roles with significant client interaction in the US. Benefits are usually more limited for contractors compared to full-time employees, with compensation often being the primary driver.

🎯 Team & Company Context

🏢 Company Culture

Industry: Technology, specifically focused on Extended Reality (XR) training and simulation solutions, with a strong presence in the Defense and Enterprise Training sectors. HTX Labs is positioned at the intersection of advanced technologies and applied learning.

Company Size: HTX Labs is a growing company, likely falling into the startup or early-stage growth phase. This typically means a dynamic, agile environment where individuals can have a significant impact.

Founded: While the founding date isn't explicitly provided, the company's focus on XR and its current market engagement suggests it is a relatively modern tech firm.

Team Structure:

• The role reports to the Director of Innovation & Design, indicating a close connection to product development and forward-thinking initiatives.

• The position requires tight integration with Product, Engineering, and Innovation & Design teams, suggesting a collaborative, cross-functional operational structure.

Methodology:

• Data-Driven Decision Making: A core methodology will involve using data analytics and UX research to inform product development, system design, and customer solutions.

• Agile & Iterative Development: Expect a fast-paced, iterative approach to development and deployment, prioritizing rapid feedback loops and continuous improvement.

• Customer-Centric Problem Solving: The company emphasizes understanding and solving mission-critical problems for its customers, integrating solutions directly into their workflows.

Company Website: https://htxlabs.com/

📝 Enhancement Note: The company's focus on XR for training, particularly for government and enterprise clients, suggests a culture that values innovation, technical excellence, and the ability to deliver tangible results in complex environments. The "Director of Innovation & Design" reporting line reinforces the forward-looking and product-centric nature of this role.

📈 Career & Growth Analysis

Operations Career Level: This role represents a senior-level, specialized position within the broader operations and technical delivery landscape. It's not a traditional GTM operations analyst but a "Forward Deployed UX Data Engineer" or "UX Data Researcher"—a hybrid technical expert. The 5+ years of experience requirement confirms this senior standing. The scope involves deep technical contribution, user understanding, and direct customer engagement.

Reporting Structure: Reporting to the Director of Innovation & Design places this role within a strategic product development and innovation function. This offers visibility into the long-term vision of HTX Labs' technology and platform, moving beyond just tactical execution.

Operations Impact: The impact is significant, directly influencing the success of customer deployments, the effectiveness of XR training solutions, and the evolution of HTX Labs' core product, EMPACT. By embedding with customers, analyzing their data, and improving user experiences, this role directly contributes to customer satisfaction, retention, and the demonstration of ROI for HTX Labs' technology.

Growth Opportunities:

• Specialization Deepening: Opportunity to become a subject matter expert in XR data analytics, immersive learning analytics, and customer-specific data challenges within the DoD and enterprise training sectors.

• Leadership in Customer Engagements: Potential to lead technical delivery for key client accounts, manage project scope, and mentor junior team members on customer-facing projects.

• Product Influence: Direct input into the product roadmap based on field insights and data, shaping the future of HTX Labs' platform.

• Transition to Full-Time: For exceptional contract performance, there may be opportunities to transition into a full-time role with expanded responsibilities and benefits.

📝 Enhancement Note: This role offers a unique growth path for individuals who excel at the intersection of technical data work, user experience, and client delivery. It's less about climbing a traditional corporate ladder and more about becoming a highly valued, specialized technical consultant and implementer.

🌐 Work Environment

Office Type: This is a fully remote position, meaning the primary work environment will be home-based for individuals located within the United States.

Office Location(s): While the role is remote, HTX Labs likely has a physical headquarters or primary operational base, but this is not a requirement for the candidate's location. The key is being U.S.-based for employment authorization.

Workspace Context:

• Remote Collaboration: The environment will heavily rely on digital collaboration tools (e.g., Slack, Zoom, project management software) for communication with internal teams and external customers.

• Self-Management: Requires a high degree of self-discipline, time management, and ability to maintain productivity in a remote setting.

• Technology Access: Candidates will need reliable internet access and a suitable home office setup to effectively manage data systems and participate in virtual meetings.

• Customer Site Visits: While primarily remote, there's a possibility of occasional travel to customer sites for critical deployments or deep dives, though the description emphasizes remote engagement.

Work Schedule: The standard work schedule is approximately 40 hours per week. However, given the customer-facing and project-driven nature of the role, flexibility will be key. This might involve accommodating different time zones for customer interactions or working slightly extended hours during critical project phases or deployment windows.

📝 Enhancement Note: The remote nature of this contract position means the candidate must be comfortable with independent work and proficient in using digital collaboration tools. The emphasis on "customer-embedded" suggests a need to be responsive and available to clients, which may require some flexibility in working hours.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A review of your resume and portfolio to assess alignment with the required skills and experience, particularly in data engineering, UX research, and customer delivery.

• Technical Interview(s): Expect in-depth discussions on data architecture, system design, querying, coding proficiency (Python/JavaScript), and your approach to solving complex data problems. This may include live coding exercises or system design challenges.

• UX/Research Interview: Focus on your methodology for user research, how you translate insights into actionable recommendations, and your experience with data visualization and reporting.

• Customer Delivery & Problem-Solving Scenario: You may be presented with hypothetical customer scenarios to gauge your ability to understand needs, architect solutions, manage ambiguity, and communicate effectively under pressure.

• Cultural Fit / Team Interview: An assessment of your ability to collaborate within a fast-paced, innovative environment and integrate with the Product, Engineering, and Design teams.

• Hiring Manager Conversation: A final discussion with the Director of Innovation & Design to cover overall fit, career aspirations, and finalize any contractual details.

Portfolio Review Tips:

• Highlight Process & Impact: For each project, clearly articulate the problem, your specific role and process, the technologies used, and the measurable impact or outcomes achieved.

• Showcase Data Systems & UX: Include examples of data architecture diagrams, database schemas, analytics dashboards, and UX research reports or case studies demonstrating insight generation.

• Demonstrate Code Proficiency: If possible, link to a GitHub repository or provide code snippets that showcase your ability to write production-grade Python or JavaScript.

• Quantify Achievements: Use metrics and data points wherever possible to demonstrate the success of your work (e.g., "Improved data processing efficiency by X%," "Identified user pain points leading to Y product changes").

• Tailor to the Role: Emphasize projects that align with XR, training data, customer-facing solutions, and rapid technical delivery.

Challenge Preparation:

• Data System Design: Be prepared to design a scalable data architecture for a hypothetical XR training application, considering data ingestion, storage, processing, and visualization.

• Problem Decomposition: Practice breaking down complex customer problems into smaller, manageable technical and research tasks.

• Insight Translation: Prepare to explain how you would turn raw user data or research findings into concrete feature requests or system improvements.

• Technical Communication: Practice explaining technical concepts and solutions clearly to both technical and non-technical audiences.

📝 Enhancement Note: The interview process for this role will be rigorous, testing both deep technical skills and the ability to apply them in a customer-centric, product-focused environment. The portfolio review is a critical component, acting as a tangible demonstration of capabilities.

🛠 Tools & Technology Stack

Primary Tools:

• Programming Languages: Python (for data analysis, scripting, backend development), JavaScript (for web integration, frontend analytics).

• Cloud Platforms: Experience with at least one major cloud provider (AWS, Azure, GCP) for data storage, compute, and managed services.

• Databases: SQL (PostgreSQL, MySQL), NoSQL databases (e.g., MongoDB, DynamoDB) may be relevant.

• Data Warehousing/Lakes: Familiarity with concepts and tools for managing large datasets.

Analytics & Reporting:

• Data Visualization Tools: Tableau, Power BI, Looker, or similar platforms for creating dashboards and reports.

• Analytics Platforms: Google Analytics, Mixpanel, Amplitude, or custom analytics frameworks.

• Statistical Software: R or Python libraries (Pandas, NumPy, SciPy) for data analysis.

CRM & Automation:

• CRM: While not explicitly mentioned, experience with CRMs (e.g., Salesforce) can be beneficial for understanding customer data pipelines.

• ETL/ELT Tools: Tools for data integration and transformation (e.g., Apache Airflow, dbt) may be relevant.

• Version Control: Git (e.g., GitHub, GitLab) for code management.

Specialized Tools:

• XR/VR/AR Development Environments: Unity or Unreal Engine knowledge is a plus.

• Learning Standards: Familiarity with LRS, LMS, SCORM, xAPI.

• Machine Learning Libraries: Scikit-learn, TensorFlow, PyTorch (if ML is a focus).

📝 Enhancement Note: The technology stack is broad, reflecting the hybrid nature of the role. Proficiency in Python and SQL is foundational. Experience with cloud platforms and data visualization tools is essential. The specific mention of XR and learning standards highlights the specialized domain.

👥 Team Culture & Values

Operations Values:

• Innovation & Pragmatism: A balance between pushing technological boundaries (XR, AI) and delivering practical, measurable solutions for customers.

• Customer-Centricity: A strong focus on understanding and solving customer needs, often through direct engagement and embedded delivery.

• Data-Driven Excellence: Commitment to using data and research to inform decisions, optimize systems, and demonstrate value.

• Agility & Speed: Thriving in fast-paced environments, making quick, sound decisions, and moving from prototype to production rapidly.

• Collaboration: Working seamlessly across Product, Engineering, and Design teams, as well as with external customer stakeholders.

Collaboration Style:

• Cross-functional Integration: Expect close collaboration with Product Managers, UX Designers, and Software Engineers to define requirements, build solutions, and iterate based on feedback.

• Customer Partnership: A style that involves active listening, clear communication, and building trust with client teams to ensure successful solution deployment and adoption.

• Knowledge Sharing: A culture that encourages sharing insights, best practices, and learnings from customer engagements to benefit the broader team and product development.

📝 Enhancement Note: The company culture appears to be geared towards high-impact, technically sophisticated work within a dynamic startup environment. The emphasis on customer embedding and cross-functional collaboration suggests a team that is both technically adept and highly communicative.

⚡ Challenges & Growth Opportunities

Challenges:

• Ambiguity in Customer Needs: Navigating diverse and sometimes unclear mission requirements within complex customer environments (e.g., DoD).

• Technical Integration Complexity: Integrating new XR and data systems with existing legacy or diverse customer IT infrastructures.

• Rapid Iteration Cycles: Balancing the need for speed and innovation with maintaining data integrity, system stability, and quality.

• Demonstrating ROI: Clearly quantifying the value and impact of XR training solutions and data insights for customers.

• Staying Current: Keeping pace with rapid advancements in XR, AI/ML, and data analytics technologies.

Learning & Development Opportunities:

• Deep Dive into XR Data: Gain specialized expertise in collecting, analyzing, and leveraging data from immersive training environments.

• Industry Exposure: Work closely with leading organizations in defense and enterprise training, understanding their unique operational challenges and data needs.

• Advanced Analytics & ML: Opportunities to apply machine learning and predictive analytics techniques to user behavior and training effectiveness data.

• Customer Success Methodologies: Develop strong skills in client management, technical consulting, and solution delivery in high-stakes environments.

📝 Enhancement Note: The challenges are inherent to working with cutting-edge technology in complex, real-world applications. The growth opportunities are substantial for individuals looking to specialize in a high-demand, future-oriented field.

💡 Interview Preparation

Strategy Questions:

• Data System Design: "Describe how you would design a scalable data architecture for an XR training platform that needs to track user performance, engagement, and learning outcomes in real-time. What technologies would you consider and why?" (Focus on architecture, scalability, data types, and integration.)

• Insight to Action: "Imagine our user research reveals a significant drop-off in engagement during a specific module of an XR training simulation. How would you investigate this using data, and what steps would you take to propose solutions to the product team?" (Focus on mixed-methods analysis and actionable recommendations.)

• Customer Delivery: "You're embedded with a new client, and their initial requirements for data collection in their XR training are vague. How do you approach clarifying these needs, defining success metrics, and ensuring successful technical delivery?" (Focus on communication, requirement gathering, and project management.)

Company & Culture Questions:

• "What interests you most about HTX Labs and our focus on XR for training, particularly within the DoD/enterprise sectors?" (Demonstrate research into the company and industry.)

• "How do you typically collaborate with Product Managers, Engineers, and Designers on technical projects?" (Highlight cross-functional teamwork.)

Portfolio Presentation Strategy:

• Narrative Flow: Structure your portfolio presentation around key projects, using a story-telling approach that highlights the problem, your solution, and the quantifiable impact.

• Technical Depth: Be prepared to dive deep into the technical aspects of your projects when asked, explaining your design choices, code, and tools.

• UX/Data Link: Clearly articulate how your data analysis and system design directly informed or improved the user experience, or vice-versa.

• Customer Focus: Frame your experience in terms of delivering value and solving problems for users or clients.

📝 Enhancement Note: The interview will likely assess your ability to connect technical expertise with user needs and business outcomes. Be ready to discuss both the "how" (technical implementation) and the "why" (user impact, business value).

📌 Application Steps

To apply for this operations position:

• Submit your application through the provided link on the HTX Labs careers portal.

• Curate Your Portfolio: Select 2-3 key projects that best showcase your expertise in data architecture, analytics, UX research, and technical delivery, especially any related to XR, training data, or client-facing solutions.

• Tailor Your Resume: Emphasize keywords from the job description such as "data engineering," "UX research," "data architecture," "customer-embedded delivery," "Python," "JavaScript," "XR," and "xAPI." Quantify your achievements with metrics wherever possible.

• Prepare Your Narrative: Practice articulating your experience and how it aligns with the hybrid nature of this role. Be ready to discuss your approach to problem-solving, data analysis, and user research in a concise and impactful manner.

• Research HTX Labs: Understand their mission, product (EMPACT), target markets (DoD, enterprise training), and recent news. This will be crucial for demonstrating interest and cultural fit.

⚠️ Important Notice: This enhanced job description includes AI-generated insights and operations industry-standard assumptions. All details should be verified directly with the hiring organization before making application decisions.

---