Realize your potential by joining the leading performance-driven advertising company!
As a Senior Data Scientist on the Algorithms team in our Tel Aviv office, you’ll play a vital role in designing and deploying machine learning models that power real-time bidding and optimize billions of daily auctions. You’ll develop advanced modeling solutions that drive bid optimization, price prediction, and auction strategy while partnering closely with Engineering, Product, and Business teams to bring research into production. Your work will directly improve advertiser performance, publisher revenue, and marketplace efficiency at massive scale.
To thrive in this role, you'll need:
- 4+ years of experience building machine learning solutions end-to-end, from research and experimentation through production.
- MSc or PhD in Computer Science, Mathematics, Statistics, Engineering, or a related quantitative field.
- Experience developing machine learning models for real-time bidding (RTB), recommendation systems, ranking, pricing, or other large-scale optimization problems.
- Strong programming skills in Python and experience working with production-grade machine learning systems.
- Strong foundation in machine learning, statistical modeling, experimentation, and data analysis.
Bonus points if you have:
- Experience with deep learning models in large-scale recommendation or advertising systems.
- Experience using AI development tools (such as Claude Code or Cursor) to accelerate experimentation and development.
How you'll make an impact:
- Design, train, and deploy machine learning models for bid optimization, price prediction, win-rate prediction, CTR/CVR estimation, calibration, and auction optimization.
- Own the full machine learning lifecycle, from research and experimentation through production deployment, A/B testing, monitoring, and continuous optimization.
- Analyze large-scale marketplace data to identify modeling opportunities and translate insights into measurable business impact.
- Partner closely with Product, Engineering, and Business teams to define and deliver scalable machine learning solutions.
- Improve the performance, scalability, and reliability of production models serving low-latency, high-throughput traffic.
- Mentor junior data scientists and contribute to technical reviews, experimentation best practices, and knowledge sharing across the team.
Why Taboola?
If you ask Taboolars what they love about working here, they’ll tell you that they’ve been empowered to realize their full potential while growing and learning from and with smart and talented people. They’ll also share more about:
Adam Singolda, Taboola Founder and CEO says:
"You can copy anything from another business but you can’t copy a company’s culture."
Well-being: Enjoy comprehensive benefits and well-being programs tailored to the region, a fully stocked kitchen, and location-specific perks.
Flexibility: We offer a hybrid work schedule with 3 days in-office, with an option to come in more often if desired.
Work with some of the biggest names: Our publisher partners include Yahoo, Condé Nast, Fox Sports, NBCU, ESPN, CBS, and E! Online. Our advertiser clients include Wells Fargo, Honda, Pinterest, and Expedia.
Ready to realize your potential?
Taboola is an equal opportunity employer and we value diversity in all forms. We are committed to creating an inclusive environment for all employees and believe such an environment is critical for success. Employment is decided on the basis of qualifications, merit, and business need.
Learn more about #TaboolaLife on LinkedIn, Facebook, Instagram, X, YouTube, & the Taboola Life Blog.
About Taboola
Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale.
Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.
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Skills Required
- 4+ years building machine learning solutions end-to-end, from research and experimentation through production
- MSc or PhD in Computer Science, Mathematics, Statistics, Engineering, or related quantitative field
- Experience developing machine learning models for real-time bidding (RTB), recommendation systems, ranking, pricing, or large-scale optimization problems
- Strong programming skills in Python and experience with production-grade machine learning systems
- Strong foundation in machine learning, statistical modeling, experimentation, and data analysis
- Experience with deep learning models in large-scale recommendation or advertising systems
- Experience using AI development tools (such as Claude Code or Cursor) to accelerate experimentation and development
What the Team is Saying
What We Do
Taboola empowers businesses to grow through performance advertising technology that goes beyond search and social and delivers measurable outcomes at scale. Taboola works with thousands of businesses who advertise directly on Realize, Taboola’s powerful ad platform, reaching approximately 600M daily active users across some of the best publishers in the world. Publishers like NBC News, Yahoo, and OEMs such as Samsung, Xiaomi and others use Taboola’s technology to grow audience and revenue, enabling Realize to offer unique data, specialized algorithms, and unmatched scale.
Why Work With Us
What sets Taboola apart? Our culture. We combine the massive data scale of a global ad-tech powerhouse with a culture anchored in empathy, non-linear growth, and trust-first flexibility. If you're looking to tackle complex AI challenges alongside brilliant, supportive peers—while being valued as a whole human being—your next chapter starts here.
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Taboola Offices
Hybrid Workspace
Employees engage in a combination of remote and on-site work.
Taboola offers flexibility and the ability to work remotely two days a week with three days in-office.
