Lead Data Scientist (AdTech)

Location: New York, United States; hybrid work environment, and only candidates local to the posting location will be considered.

Salary: $223,000–$272,000 for New York-based candidates, based on experience, skills, and qualifications.

Company

Mobile advertising technology company providing an end-to-end platform that connects telecoms, OEMs, advertisers, publishers, and consumers across devices.

What you will do

• Translate complex business challenges into multi-quarter data science roadmaps that influence product strategy and commercial outcomes.
• Define methodology and standards for centralized experimentation, causal inference, A/B testing, and hypothesis validation.
• Architect production-grade statistical and machine learning models for bidding and user acquisition optimization, audience segmentation, lifetime value, and attribution.
• Direct time-series forecasting and real-time event-processing strategies for automated decisioning, yield optimization, and recommendation engines.
• Partner with ML Infrastructure and Data Engineering leads on model deployment, monitoring, and integration into the Next Best Action framework.
• Mentor data scientists, establish technical standards, and communicate findings to executive stakeholders.

Requirements

• 8+ years of progressive experience in data science, quantitative analysis, or machine learning, including technical leadership in AdTech, two-sided marketplaces, or consumer-scale data platforms.
• Expertise in advanced statistical modeling, causal inference, experimental design, and machine learning architectures.
• Expert fluency in Python or R and SQL.
• Experience handling petabyte-scale data in cloud infrastructure such as Databricks, Spark, Snowflake, AWS, or GCP.
• Ability to design scalable tools, reusable metrics frameworks, and automated modeling pipelines.
• Strong cross-functional communication and technical strategy leadership across product, engineering, and business organizations.

Nice to have

• Experience architecting metrics semantic layers or enterprise experimentation tools.
• Expertise in real-time bidding auctions, algorithmic yield management, or advanced attribution.
• Master’s or Ph.D. in Statistics, Computer Science, Economics, Operations Research, Physics, or another quantitative field.

Culture & Benefits

• Hybrid work environment for candidates local to New York.
• Comprehensive benefits package.
• Stock options, unlimited paid time off, and performance-based bonus.
• Focus on diversity, inclusion, and equitable compensation.
• Global office presence across the United States, United Kingdom, Germany, Singapore, Israel, and other locations.