Lead Quantitative UX Researcher

📍 Job Overview

Job Title: Lead Quantitative UX Researcher

Company: PrizePicks

Location: Atlanta, GA (Preferred) / Remote (US-based)

Job Type: Full-Time

Category: User Experience Research / Product Analytics

Date Posted: June 2, 2026

Experience Level: 8+ Years (Senior/Lead)

Remote Status: Remote OK (US-based)

🚀 Role Summary

• Spearhead the quantitative UX research strategy and data roadmap for key product lines, aligning user insights with business objectives and customer satisfaction metrics.

• Design, execute, and analyze complex, multi-method quantitative research studies, including A/B testing, advanced surveys, user profiling, and behavioral modeling.

• Transform high-volume telemetry data and survey results into compelling, actionable strategic narratives that inform leadership decisions and de-risk product development.

• Collaborate closely with Product Management, Design, Engineering, and Product Analytics to integrate user insights throughout the product lifecycle, driving product evolution and innovation.

📝 Enhancement Note: This role is positioned as a Lead Individual Contributor (IC) with significant strategic influence. The emphasis on "quantitative UX research," "telemetry log analysis," and "statistical profiling" indicates a strong focus on data-driven product decisions, making it a critical role within a fast-paced, data-informed organization like PrizePicks. The target candidate will not only execute research but also define the research agenda and mentor others.

📈 Primary Responsibilities

• Own Research Strategy & Roadmap: Define and execute the quantitative UX research strategy and data roadmap for major product areas, ensuring alignment with business priorities, core customer satisfaction (CSAT) indexes, and product goals.

• Design & Execute Complex Studies: Independently scope and lead advanced, multi-method quantitative research studies, including but not limited to A/B testing experimentation frameworks, complex on-platform surveys, MaxDiff analyses, user segmentation, and behavioral modeling.

• Synthesize & Strategize: Analyze and synthesize complex log data, high-volume survey results, and other quantitative data sources into clear, actionable insights and strategic storytelling artifacts that inform leadership decisions and mitigate product discovery risks.

• Cross-Functional Partnership: Collaborate directly with Product Managers, Designers, and Engineers to identify critical research questions, define key user journeys, and establish shared understanding of user needs and behaviors early in the product development lifecycle.

• Methodological Innovation: Continuously innovate within existing quantitative methodologies to enhance team efficiency, accelerate operational pace, and improve the accuracy and impact of user experience measurement capabilities.

• Mentorship & Guidance: Actively mentor junior and mid-level qualitative and mixed-methods UX researchers, advocating for rigorous, evidence-based research practices and guiding colleagues on best practices in survey design and quantitative fundamentals.

• Champion Best Practices: Support the maintenance of internal insights repositories, democratize access to data and analysis tools across teams, and champion user experience metrics as direct predictors of core business outcomes.

📝 Enhancement Note: The responsibilities highlight a blend of strategic ownership, hands-on execution of advanced research methods, and leadership/mentorship. The emphasis on "synthesizing complex log data" and "actionable strategic narratives" points to the need for strong analytical and communication skills beyond just data collection.

🎓 Skills & Qualifications

Education:

• Bachelor’s, Master’s, or PhD in Psychology, Economics, Neuroscience, Human Factors Engineering, Human-Computer Interaction (HCI), Computational Social Science, or a related quantitative field.

Experience:

• 8+ years of relevant applied experience in quantitative UX research, product data science, or an equivalent analytical consumer insights field.

Required Skills:

• Statistical Modeling: Deep general knowledge of probability and advanced statistical modeling skills (e.g., GLM, multi-variable regression, Bayesian statistics) applied to large, unstructured datasets. Ability to educate non-experts on data nuances.

• Technical Proficiency: Expert proficiency in SQL for data querying and manipulation. Expert proficiency in specialized applied programming packages such as R or Python for custom analytics, statistical analysis, and data manipulation.

• Survey Domain Mastery: Comprehensive expertise in advanced survey design, robust user sampling workflows, data stratification, and experience with leading intercept deployment tools (e.g., Qualtrics, Dscout).

• Research Methodologies: Proven experience designing and conducting A/B testing experimentation frameworks, complex on-platform surveys, MaxDiff studies, user profiling, and behavioral modeling.

• Data Synthesis & Storytelling: Ability to synthesize complex data into clear, compelling, and actionable insights and strategic narratives that drive leadership decisions.

• Cross-Functional Collaboration: Proven ability to partner effectively with Product Managers, Designers, and Engineers to inform product strategy and development.

Preferred Skills:

• Experience in the gaming, sports, or fast-paced consumer tech industry.

• Familiarity with telemetry log analysis tools and techniques.

• Experience with data visualization tools (e.g., Tableau, Looker) for communicating findings.

• Mentorship or team leadership experience.

📝 Enhancement Note: The emphasis on specific statistical techniques (GLM, Bayesian) and programming languages (R, Python) alongside SQL signifies a highly analytical and technical role. The requirement for "expert proficiency" suggests that candidates should be able to demonstrate deep practical application of these skills. The "Impact Portfolio" requirement is key, indicating that candidates must showcase tangible results rather than just theoretical knowledge.

📊 Process & Systems Portfolio Requirements

Portfolio Essentials:

• End-to-End Execution: Showcase case studies demonstrating the complete lifecycle of quantitative research projects, from initial problem definition and methodology selection to data analysis and actionable insight delivery.

• Professional Visual Deliverables: Include examples of high-quality visual outputs such as charts, matrices, frameworks, and dashboards that effectively communicate complex data and findings to diverse audiences.

• Measurable Impact Demonstration: Clearly articulate and quantify the business or metric-driven impact of your research. This should include examples of how your insights led to product improvements, increased user engagement, or positive business outcomes.

• Methodological Diversity: Present a range of quantitative methodologies employed, highlighting your adaptability and expertise in selecting the right approach for different research questions (e.g., A/B testing, surveys, segmentation, behavioral analysis).

Process Documentation:

• Research Planning & Design: Demonstrate experience in defining research objectives, identifying key hypotheses, selecting appropriate quantitative methods, designing robust sampling plans, and crafting effective survey instruments.

• Data Analysis & Synthesis: Provide examples of how you handle large datasets, perform advanced statistical analyses, and synthesize findings into strategic recommendations. Proficiency in tools like R, Python, and SQL is critical here.

• Insight Communication & Integration: Show how you translate complex data into clear, compelling narratives and effectively communicate these insights to cross-functional teams and leadership to influence product strategy and decisions.

📝 Enhancement Note: The "Impact Portfolio" requirement is central. Candidates must be prepared to demonstrate not just what they did, but the measurable results of their work. This means quantifying impact on metrics like CSAT, conversion rates, engagement, or revenue, and structuring case studies to clearly show the problem, approach, results, and business impact.

💵 Compensation & Benefits

Salary Range: $150,000 - $185,000 Annually

Benefits:

• Company-subsidized medical, dental, & vision plans

• 401(k) plan with company match

• Annual bonus potential

• Flexible Paid Time Off (PTO) with a strong encouragement to take at least 2 weeks annually for work-life balance.

• Generous paid leave programs, including 16-week paid parental leave and disability benefits.

• Workplace flexibility and modern work schedules focused on achieving results.

• Company-wide in-person events and team outings.

• Lifestyle enhancement program.

• Company-provided equipment (Windows & Mac options).

Working Hours:

• Standard full-time hours are assumed, likely around 40 hours per week. The company emphasizes flexibility and results over strict hours clocked, supporting a modern work schedule.

📝 Enhancement Note: The salary range is competitive for a Lead Quantitative UX Researcher role in a major US city or for a remote senior position. The inclusion of an annual bonus and comprehensive benefits package, especially the 16-week parental leave, indicates a strong commitment to employee well-being and retention. The mention of "local cost of living" for salary determination is a key point for remote candidates.

🎯 Team & Company Context

🏢 Company Culture

Industry: Daily Fantasy Sports (DFS) / Sports Technology

Company Size: Over 550 employees. This indicates a growing, dynamic company that has achieved significant scale but likely retains some of the agility of a smaller organization.

Founded: PrizePicks is recognized as the fastest-growing sports company in North America, suggesting a culture of rapid innovation, execution, and ambition.

Team Structure:

• The quantitative UX researcher will be part of a growing UX research team, likely reporting into a Head of UX Research or a Director of Product.

• This role involves close collaboration with Product Management, Design, Engineering, Product Analytics, and Consumer Insights teams, highlighting a highly cross-functional environment.

Methodology:

• Data-Driven Decision Making: PrizePicks emphasizes using data ("telemetry log analysis," "statistical profiling," "quantitative research") to inform product strategy and evolution.

• User-Centricity: The core function of the role is to be the voice of the user, ensuring product decisions are grounded in user needs and behaviors.

• Agile & Iterative: As a fast-growing tech company in the sports sector, the culture likely embraces agility, rapid iteration, and a test-and-learn approach.

• Inclusivity: The company actively values individuals from diverse backgrounds and explicitly mentions this as part of its culture.

Company Website: [PrizePicks Website URL] (Assuming this would be provided or easily found)

📝 Enhancement Note: The "fastest-growing" and "leading platform" descriptors suggest a high-performance, results-oriented culture. The emphasis on data and user insights indicates that operations and product teams are expected to be analytical and strategic.

📈 Career & Growth Analysis

Operations Career Level: Lead Individual Contributor (IC)

Reporting Structure:

• The Lead Quantitative UX Researcher will likely report to a Director-level individual (e.g., Director of UX Research, Director of Product) or potentially a VP.

Operations Impact:

• This role has a direct impact on product strategy, user experience, and ultimately, business outcomes like customer acquisition, retention, engagement, and revenue growth within the Daily Fantasy Sports platform.

Growth Opportunities:

• Deepening Expertise: Further specialization in advanced statistical modeling, machine learning applications in UX, or specific areas of behavioral economics relevant to consumer behavior.

• Expanding Influence: Taking on research strategy for broader product portfolios or new market initiatives.

• Mentorship & Team Building: Potentially evolving into a formal team lead or manager role as the UX research function grows, focusing on building and developing a high-performing team.

• Cross-Functional Leadership: Developing stronger strategic partnerships and influencing product roadmaps across larger segments of the business.

📝 Enhancement Note: The "Lead" title strongly suggests a path for growth within an IC track, focusing on increasing scope of influence and strategic impact, rather than necessarily moving into people management immediately. The company's rapid growth provides ample opportunities for individuals to expand their responsibilities.

🌐 Work Environment

Office Type: Hybrid/Remote-First with a preferred office hub.

Office Location(s):

• Atlanta, GA is the preferred location.

Workspace Context:

• Collaborative Environment: The role requires extensive collaboration with Product, Design, and Engineering teams, suggesting an open and communicative workspace, whether in-person or virtual.

• Technology-Rich: Expect access to modern collaboration tools, data analysis software, and potentially dedicated research platforms.

• Data-Centric: The environment will likely be highly focused on data, analytics, and evidence-based decision-making, fostering a culture where research insights are valued and acted upon.

Work Schedule:

• The company promotes "workplace flexibility and modern work schedules focused on getting the job done, not hours clocked." This suggests a results-oriented approach where employees have autonomy over their schedules, provided they meet project deadlines and collaborate effectively.

📝 Enhancement Note: The "Remote OK" status with a "preferred" location indicates flexibility but also a potential preference for candidates who can occasionally engage in-person if based in Atlanta. The "modern work schedules" implies trust and autonomy for employees.

📄 Application & Portfolio Review Process

Interview Process:

• Initial Screening: A recruiter or hiring manager will review applications and conduct an initial phone screen to assess basic qualifications and cultural fit.

• Technical/Skills Assessment: This will likely involve a deep dive into your quantitative research methodologies, statistical knowledge, and technical proficiency (SQL, R/Python). This could be an interview with a peer researcher or manager.

• Portfolio Review: A critical stage where you will present 1-2 key case studies from your portfolio, demonstrating your end-to-end research process and impact.

• Cross-Functional Interviews: Interviews with key stakeholders (Product Managers, Designers, Engineers) to assess collaboration skills, strategic thinking, and ability to translate research into product action.

• Lead/Manager Interview: A final discussion with the hiring manager or a senior leader to discuss strategic vision, leadership potential, and overall fit.

Portfolio Review Tips:

• Focus on Impact: For each case study, clearly articulate the business problem, your quantitative approach, the key findings, and most importantly, the measurable impact your research had on the product or business metrics.

• Quantify Everything: Use numbers, percentages, and data points to demonstrate the scale of the problem, the rigor of your study, and the magnitude of the results.

• Tell a Story: Structure your presentation logically, guiding the interviewers through the research journey and highlighting your critical contributions.

• Showcase Technical Skills: Be prepared to discuss the statistical techniques used, the data sources, and how you leveraged tools like SQL, R, or Python.

• Highlight Strategic Thinking: Explain why you chose certain methodologies and how your insights informed strategic decisions.

• Prepare for Questions: Anticipate questions about your methodology choices, data limitations, alternative approaches, and how you handled ambiguity.

Challenge Preparation:

• While not explicitly mentioned, be prepared for a potential take-home assignment or a live case study discussion. This might involve analyzing a dataset, critiquing a research plan, or outlining a quantitative research strategy for a given product scenario.

• Practice articulating complex statistical concepts in simple terms for non-technical stakeholders.

📝 Enhancement Note: The portfolio review is explicitly called out as a key requirement. Candidates must have a well-developed portfolio ready to present, focusing on quantitative impact and strategic application. The ability to clearly communicate complex data and its business implications will be paramount.

🛠 Tools & Technology Stack

Primary Tools:

• SQL: Essential for data extraction and manipulation from databases.

• R or Python: Required for advanced statistical analysis, modeling, and data manipulation. Proficiency in specialized packages for statistical modeling (e.g., stats, lme4, rstan in R; statsmodels, scikit-learn in Python) is expected.

• Survey Platforms: Expertise with tools like Qualtrics or similar advanced survey deployment and analysis platforms.

• Data Visualization Tools: Proficiency with tools like Tableau, Looker, Power BI, or libraries within R/Python (e.g., ggplot2, matplotlib, seaborn) for creating impactful charts and dashboards.

Analytics & Reporting:

• Telemetry/Log Analysis Tools: Experience with tools or methods for analyzing user behavior data from application logs.

• A/B Testing Frameworks: Understanding and experience with designing, running, and analyzing A/B tests.

CRM & Automation:

• While not directly a CRM role, understanding how user data integrates with CRM or marketing automation platforms might be beneficial for understanding the broader customer journey.

📝 Enhancement Note: The tech stack emphasizes deep analytical capabilities. Candidates must be comfortable with advanced statistical programming and data querying. The expectation is not just to use these tools, but to leverage them for complex analytical tasks and strategic insights.

👥 Team Culture & Values

Operations Values:

• Data-Driven: A strong emphasis on using data and evidence to inform decisions and measure impact.

• User-Centricity: A commitment to understanding and prioritizing user needs and experiences.

• Innovation & Growth: A drive to innovate, grow rapidly, and be at the forefront of the DFS industry.

• Collaboration: Valuing teamwork and cross-functional partnerships to achieve collective success.

• Inclusivity: Fostering an environment where diverse backgrounds and perspectives are welcomed and valued.

• Efficiency & Pace: As a fast-growing company, there's likely an appreciation for operational efficiency and the ability to move at a quick pace.

Collaboration Style:

• Cross-Functional Integration: Expect close collaboration with Product, Design, and Engineering teams, requiring strong communication and the ability to translate research findings into actionable product requirements.

• Evidence-Based Advocacy: The role involves advocating for user needs based on rigorous quantitative evidence, requiring strong presentation and persuasion skills.

• Mentorship & Knowledge Sharing: A culture that supports learning and development, where senior members contribute to the growth of others.

📝 Enhancement Note: The company culture appears to be a blend of high performance, data-driven decision-making, and a people-centric approach that values diversity and collaboration. Candidates should be comfortable in a fast-paced, evolving environment.

⚡ Challenges & Growth Opportunities

Challenges:

• Balancing Rigor with Pace: Ensuring robust quantitative research methodologies are applied effectively within a fast-paced product development cycle.

• Synthesizing Vast Data: Managing and extracting meaningful insights from large, potentially complex, and sometimes unstructured log and survey data.

• Influencing Diverse Stakeholders: Translating complex statistical findings into clear, compelling narratives that resonate with stakeholders across Product, Design, Engineering, and Leadership.

• Defining and Measuring Success: Establishing clear, measurable UX metrics that directly correlate with business objectives and effectively tracking these over time.

• Mentoring and Upskilling: Balancing individual research contributions with the responsibility of mentoring and elevating the quantitative skills of the broader research team.

Learning & Development Opportunities:

• Advanced Methodologies: Deepen expertise in areas like causal inference, advanced segmentation techniques, or predictive modeling for user behavior.

• Industry Trends: Stay abreast of emerging best practices in quantitative UX research, data science, and user analytics within the sports/gaming tech space.

• Strategic Impact: Grow influence by taking on larger, more strategic product areas and contributing to long-term product vision.

• Leadership Development: Develop mentorship and coaching skills, potentially leading initiatives for the research team.

• Cross-Functional Acumen: Enhance understanding of business operations, product strategy, and engineering processes to better align research efforts.

📝 Enhancement Note: The challenges are typical for a senior quantitative role in a growing tech company, emphasizing the need for strong analytical skills, strategic thinking, and effective communication. The growth opportunities are well-defined for an IC track.

💡 Interview Preparation

Strategy Questions:

• "Describe a time you had to design a complex quantitative research study to answer a critical product question. What were your hypotheses, methodology, and outcomes?" (Focus on methodology, statistical rigor, and impact).

• "How do you approach synthesizing large volumes of telemetry data into actionable insights for non-technical stakeholders?" (Focus on storytelling, data simplification, and actionable recommendations).

• "Imagine we're considering a major change to our core game mechanics. What quantitative research approach would you recommend, and why?" (Focus on strategic thinking, methodology selection, and risk mitigation).

Company & Culture Questions:

• "What excites you about PrizePicks and the DFS industry?" (Demonstrate research into the company and industry).

• "How do you approach mentoring junior researchers or sharing your quantitative expertise with a team?" (Highlight leadership and collaboration skills).

Portfolio Presentation Strategy:

• Structure is Key: For each case study, follow a clear narrative: Problem -> Research Question -> Methodology (including sample size, sampling method, statistical techniques) -> Key Findings -> Actionable Insights -> Business Impact (quantified).

• Visuals Matter: Use clean, professional slides with clear charts and graphs that support your narrative. Avoid overwhelming slides with text.

• Be Prepared to Dig Deep: Interviewers may ask detailed questions about your statistical methods, data cleaning processes, or how you handled specific challenges.

• Quantify Impact: This cannot be stressed enough. Be ready to state the percentage increase in conversion, reduction in churn, or uplift in engagement directly attributable to your research.

• Showcase Strategic Thinking: Explain why you made certain methodological choices and how your findings directly informed strategic product decisions.

📝 Enhancement Note: Preparation should focus on showcasing not just technical expertise, but also strategic thinking, communication skills, and the ability to drive tangible business impact through quantitative research. The portfolio is the primary tool for demonstrating this.

📌 Application Steps

To apply for this Lead Quantitative UX Researcher position:

• Submit your application through the PrizePicks careers portal or the provided link.

• Customize your Resume: Highlight your experience with quantitative UX research, statistical modeling, SQL, R/Python, survey design, and A/B testing. Quantify your achievements and impact wherever possible, using keywords from the job description.

• Prepare Your Portfolio: Select 1-2 of your strongest quantitative research case studies that demonstrate end-to-end execution and measurable business impact. Ensure they are polished, visually appealing, and ready for presentation. Be prepared to discuss the statistical methods and business outcomes in detail.

• Research PrizePicks: Understand their product, their position in the DFS market, and their stated company values. Consider how your quantitative research skills can directly contribute to their growth and success.

• Practice Interview Responses: Prepare for common quantitative UX research interview questions, focusing on articulating your process, insights, and impact clearly and concisely. Rehearse your portfolio presentation.

⚠️ 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.

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