Lead Quantitative UX Researcher

Google; Seattle (WA); On-site; USD 188,000 - 275,000; Full time

Benefits offered by this job

Health, dental, vision, life, and/disb

401(k) with company match

Paid time off 20 days/yr

Sick time 40 hours/yr (Seattle 69)

Maternity leave 28-30 weeks

Baby Bonding Leave 18 weeks

13 paid holidays/yr

Job summary

Google seeks a Quantitative User Experience Researcher (Quant UXR) to join a multi-disciplinary team and collaborate closely with Engineering and Product Management to create industry-leading, innovative products.

You will drive impact at all stages of development by investigating user behavior through empirical methods like logs analysis, survey research, and regression, blending education from Computer Science to Psychology with statistical proficiency and programming skills.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 8 years of experience working with SQL in applied research settings for consumer products.
• Experience with data manipulation and computational statistics using Python, R, MATLAB, C++, Java, or Go.

Responsibilities

• Influence stakeholders across organizations to gain support for research-based, user-centric solutions.
• Own project priorities in alignment with product goals, and oversee allocation of resources within the project.
• Drive ideas to improve products and services through research-driven insights and recommendations.
• Lead teams to define and evaluate product, service, and ecosystem impact.
• Own idea and strategy discussions through research by analyzing, consolidating, or synthesizing user, product, service, or business needs.

Skills

SQL

Python

R

C++

Education

Bachelor's degree or equivalent practical experience

Job description

Google seeks a Quantitative User Experience Researcher (Quant UXR) to join a multi-disciplinary team and collaborate closely with Engineering and Product Management to create industry-leading, innovative products.

You will drive impact at all stages of development by investigating user behavior through empirical methods like logs analysis, survey research, and regression, blending education from Computer Science to Psychology with statistical proficiency and programming skills.