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Employment type in the employer’s posting: Full-timeFrom the employer’s posting
Design and build models for supply-side monetization optimization, user lifetime-value, retention, and ARPU predictions, while measuring revenue impact.
Analyze large-scale event data and maintain metric foundations.
Partner with cross-functional teams to deploy models into production.
Responsibilities: Design and build models for supply-side monetization optimization, user lifetime-value, retention, and ARPU predictions, while measuring revenue impact. Analyze large-scale event data and maintain metric foundations.
Design and build models for supply-side monetization optimization, user lifetime-value, retention, and ARPU predictions, while measuring revenue impact. Analyze large-scale event data and maintain metric foundations. Partner with cross-functional teams to deploy models into production.
Analyze large-scale event data and maintain metric foundations. Partner with cross-functional teams to deploy models into production. Communicate findings and business impact to stakeholders.
4+ years in data science / ML applied to a data-heavy, revenue-facing domain - ad-tech, programmatic monetization, marketplaces, pricing, or a comparable real-money optimization problem.
Hands-on experience with publisher-side monetization/yield optimization, header bidding, or price-floor / seller-side auction optimization specifically.
Ability to design experiments that measure model effectiveness in production, and to own the definitions (metrics, identity, attribution) they rest on.
Familiarity with the Prebid stack (client & server).
Experience integrating models into production systems with engineering, in a fast, iterative environment.
Prior experience mentoring or leading a small data-science team.
From the employer’s posting.
Actively hiringFirst seen by us today, still listed, and not a repost of an earlier posting.
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Day 0
Early. Similar jobs usually come down between day 7 and day 57.
From 10,903 similar postings that came down. Coming down is not always a hire.
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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• Strong causal-inference and experimentation skills. This is the core of the role. • Fluent SQL on large event datasets and hands-on Python for modeling and analysis. • Solid grounding in the relevant ML families - regression, tree-based models, online optimization / multi-armed & contextual bandits, and classification/segmentation.
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New Data Scientist postings at the employers we follow are down 6% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Minute is a global technology and content company built for the future of sports consumption. Minute’s proprietary technology platform enables the creation, distribution, and monetization of digital content experiences, powering Minute’s portfolio of trusted content brands, including Sports Illustrated, The Players' Tribune, and FanSided, as well as hundreds of sports leagues, teams, broadcasters, third-party publishers, and advertisers. The technology platform includes (i) STN Video, an online video platform (OVP) that provides access to a robust sports highlights rights portfolio. Minute is building the future of how the world connects with sport, powered by innovation, shared globally, and trusted by millions of fans and the partners we serve. For more information, visit www.minutegroup.com.
The Role:
We’re looking for an experienced, rigorous Data Scientist to join our monetization data team in Tel Aviv. You’ll lead dynamic price-floor optimization strategies for programmatic display advertising across our global inventory, build models and experiments that determine which on-page experiences we show each user, and develop strategies to maximize user lifetime value while strengthening engagement and retention. You’ll also shape and manage the roadmap for our internal experimentation platform, enabling rigorous testing across the business. This is publisher-side data science, focused on our own audiences and those of our partners. The bar that matters most here is measurement, proving credibly that a change actually moved revenue before it ships.
Responsibilities:
• Design and build models for supply-side monetization optimization, user lifetime-value, retention, and ARPU predictions, while measuring revenue impact.
• Analyze large-scale event data and maintain metric foundations.
• Partner with cross-functional teams to deploy models into production.
• Communicate findings and business impact to stakeholders.
• Provide technical leadership and mentorship.
• Monitor industry trends in programmatic advertising and ad-tech.
• 4+ years in data science / ML applied to a data-heavy, revenue-facing domain - ad-tech, programmatic monetization, marketplaces, pricing, or a comparable real-money optimization problem.
• Strong causal-inference and experimentation skills. This is the core of the role.
• Fluent SQL on large event datasets and hands-on Python for modeling and analysis.
• Solid grounding in the relevant ML families - regression, tree-based models, online optimization / multi-armed & contextual bandits, and classification/segmentation.
• In-depth understanding of programmatic advertising from the supply side - RTB, auction mechanics, header bidding, price floors, and how publisher yield is actually made.
• Ability to design experiments that measure model effectiveness in production, and to own the definitions (metrics, identity, attribution) they rest on.
• Experience integrating models into production systems with engineering, in a fast, iterative environment.
• Proven ability to architect and scale models processing high-volume, real-time event streams.
• Excellent communication - able to turn a complex monetization result into a clear recommendation a non-technical stakeholder can decide on.
• Fluent English, written and spoken.
Advantageous:
• Hands-on experience with publisher-side monetization/yield optimization, header bidding, or price-floor / seller-side auction optimization specifically.
• Familiarity with the Prebid stack (client & server).
• Subscription/membership/LTV modeling - retention, churn, and balancing recurring revenue against ad revenue.
• Working knowledge of GA4 / behavioral analytics and first-party identity resolution.
• Prior experience mentoring or leading a small data-science team.
Benefits:
We're not sure you're 100% qualified, but are you up for the challenge? We want you to apply!
Minute is committed to creating a diverse and inclusive work environment and is proud to be an equal-opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Check the URL and email address of any correspondence with Minute. If it is not from @minutegroup.com, treat it as fraudulent. To learn how to protect yourself from recruitment fraud, click here.
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Tel Aviv
- Fun company events and celebrations. - Community involvement opportunities, both in-person and remote. We're not sure you're 100% qualified, but are you up for the challenge? We want you to apply!
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