Aimed at mid-level data scientists who combine mobile app analytics with causal inference expertise in a remote-friendly tech environment.
Derived from job-description analysis by Serendipath's career intelligence engine.
Original posting from Ziprecruiter via Greenhouse
We offer a hybrid work environment. Most US-based positions can also be performed remotely (any exceptions will be noted in the Minimum Qualifications below.)
Our Mission:
To actively connect people to their next great opportunity.
Who We Are:
ZipRecruiter is a leading online employment marketplace. Powered by AI-driven smart matching technology, the company actively connects job seekers with millions of businesses of all sizes through innovative mobile app, web, and email services, as well as partnerships with the best job sites on the web. ZipRecruiter has the #1 rated job search app on iOS & Android.
Summary:
As a Decision Scientist II supporting the Mobile App team, you will partner closely with product management, engineering, and design to shape and optimize the mobile user experience across acquisition, engagement, and retention. You will leverage rigorous analysis, experimentation, and causal inference to evaluate product performance, uncover user behavior insights, and identify opportunities to improve app engagement and growth. You will translate insights into product strategy, prioritize high-impact initiatives, and help deliver seamless mobile experiences that drive both business growth and job seeker success.
Key Focuses:
Define KPIs and create reports and dashboards against large data sets to track performance.
Turn ambiguous questions into clear analytical problems and solve them using data.
Become deeply familiar with product data, understanding its limitations and caveats, to support development and growth.
Design, execute, and analyze experiments that drive product growth and improvement.
Create readable and informative data visualizations, documentation, and presentations to communicate insights to stakeholders and executives.
Minimum Qualifications:
Bachelor's degree in a quantitative field such as mathematics, computer science, statistics, or economics (or equivalent experience)
3+ years of product analytics experience (optional: in a product/engineering/tech environment)
Experience designing experiments, testing, and utilizing statistical principles to inform business decisions
Proficient in statistical computing and scripting languages such as Python, R, SQL
Preferred Qualifications:
Master’s or Ph.D. in a quantitative field such as mathematics, computer science, operations research, or economics
In-depth knowledge and hands-on experience in various areas, including probability and statistics theory, causal inference, experimental design and analysis, synthetic control, product ecosystems, and Bayesian inference
Experience in product analytics with a focus on mobile apps or building zero-to-one products
As part of our team you'll enjoy:
Competitive salary
Exceptional benefits package
Flexible Vacation & Paid Time Off
Employer-matched 401(k) plan
#LI-Remote
The US base salary range for this full-time position is $130,000-$155,000. Our salary ranges are determined by role, level, and location, and the range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location, role-related knowledge and skills, depth of experience, relevant education or training, and additional role-related considerations.
Depending on the position offered, equity, bonuses, commission, or other forms of compensation may also be provided as part of a total compensation package, in addition to a full range of medical, financial, and other benefits.
ZipRecruiter is proud to be an equal opportunity employer and provides equal employment opportunities (EEO) to all employees and applicants without regard to race, color, religion, sex, national origin, age, disability, veteran status, sexual orientation, gender identity or genetics.
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