Data Scientist - Quantitative Research

We are a technology solutions firm headquartered in Bellevue, Washington, with a strong presence across the United States. Unified by a shared passion for solving complicated problems, our people are our greatest asset. We use technology as a tool to bridge the gap between strategy and execution, powered by the knowledge, skills, and the expertise of our teams, who all have unique perspectives and years of experience across multiple industries.

We’re bold, smart, agile, and fun.

Blueprint helps organizations unlock value from existing assets by leveraging cutting‑edge technology to create additional revenue streams and new lines of business. We connect strategy, business solutions, products, and services to transform and grow companies.

At Blueprint, we believe in the power of possibility and are passionate about bringing it to life. Whether you join our bustling product division, our multifaceted services team or you want to grow your career in human resources, your ability to make an impact is amplified when you join one of our teams. You’ll focus on solving unique business problems while gaining hands‑on experience with the world’s best technology.

We believe in unique perspectives and build teams of people with diverse skillsets and backgrounds. At Blueprint, you’ll have the opportunity to work with multiple clients and teams, such as data science and product development, all while learning, growing, and developing new solutions. We guarantee you won’t find a better place to work and thrive than at Blueprint.

In this role, you will serve as a senior quantitative researcher, designing and analyzing large‑scale studies to inform product, design, and operational decisions that impact employee experience. You will act as an internal research partner, applying rigorous statistical and experimental methods to understand behavior, measure outcomes, and generate actionable insights. This role emphasizes survey research, inferential statistics, and close collaboration with cross‑functional stakeholders to improve tools, services, and environments used at scale.

• Design, execute, and analyze large‑scale quantitative studies, including surveys, experiments, and observational research
• Apply inferential statistical methods such as regression analysis, hypothesis testing, and multivariate techniques to answer complex research questions
• Develop and implement sampling strategies, weighting approaches, and data quality checks to ensure statistical rigor and validity
• Analyze complex datasets using statistical programming languages and translate results into clear, actionable insights
• Communicate findings effectively to cross‑functional partners, including product, design, and research stakeholders
• Translate quantitative insights into practical recommendations that inform strategy, design decisions, and product improvements
• Collaborate with researchers and designers to refine research questions, measurement approaches, and success metrics
• Document methodologies, assumptions, limitations, and analytical decisions to support transparency and reproducibility
• Contribute to ongoing research programs through standardized metrics, dashboards, and analytical frameworks where appropriate

• Master’s degree in a quantitative field such as statistics, psychology, economics, data science, sociology, or a related discipline
• 5–7 years of professional experience conducting quantitative analysis or research, ideally in a product, UX, or applied research environment
• Strong foundation in inferential statistics and applied quantitative methods
• Demonstrated experience designing and analyzing surveys or large‑scale quantitative studies
• Proficiency in statistical programming using tools such as Python or R
• Experience working with survey data, including questionnaire design, sampling, and weighting
• Ability to clearly explain complex analyses and findings to non‑technical audiences
• Strong analytical thinking, attention to detail, and problem‑solving skills
• Proven ability to collaborate effectively in cross‑functional, interdisciplinary teams

• Backgroun…