Lead Data Scientist
About AirOps
Today thousands of leading brands and agencies use AirOps to win the battle for attention with content that both humans and agents love.
We’re building the platform and profession that will empower a million marketers to become modern leaders — not spectators — as AI reshapes how brands reach their audiences.
We’re backed by awesome investors, including Unusual Ventures, Wing VC, Founder Collective, XFund, Village Global, and Alt Capital, and we’re building a world-class team with in-person hubs in San Francisco, New York, and Montevideo, Uruguay.
About the Role
As Lead Data Scientist at AirOps, you'll shape how brands win in AI-driven search environments through advanced machine learning and data science. This role combines technical depth with strategic thinking: you'll build production-grade ML systems that directly impact how companies create and optimize content for AI agents and improve their search visibility. You'll work at the intersection of NLP, search algorithms, and large language models to create solutions that help content teams drive measurable business results.
This is a hands-on leadership position where you'll both architect systems and write code. You'll partner with product, engineering, and customer success teams to identify opportunities where ML can transform our platform's capabilities. Your work will directly influence how thousands of brands adapt to the rapidly changing search landscape where AI shapes discovery and engagement.
Key Responsibilities
Technical Leadership: Design and deploy end-to-end machine learning systems including NLP models, search and recommendation algorithms, and LLM-based applications.
Search and Content Intelligence: Build ML systems that analyze AI search behavior, identify content opportunities, and predict performance across different AI-driven platforms. Create algorithms that help brands understand and optimize for how AI agents discover and rank content.
Cross-functional Partnership: Collaborate with product managers to translate business requirements into technical solutions.
Qualifications
5+ years building production machine learning systems with demonstrated business impact; strong background in NLP and search/recommendation systems required
Deep expertise across ML approaches: classical models (XGBoost, random forests), modern deep learning architectures (transformers, graph neural networks), and reinforcement learning systems
Proven ability to take models from research to production, including optimization for latency and cost at scale
Experience with ML infrastructure and tooling: model serving frameworks, experiment tracking, feature stores, and monitoring systems
Track record of technical leadership: influencing architecture decisions, improving team practices, and driving cross-functional projects without direct authority
Excellent communication skills with ability to explain complex technical concepts to non-technical stakeholders and align ML initiatives with business outcomes
Our Guiding Principles
Extreme Ownership
Quality
Curiosity and Play
Make Our Customers Heroes
Respectful Candor
Benefits
Equity in a fast-growing startup
Competitive benefits package tailored to your location
Flexible time off policy
Generous parental leave
A fun-loving and (just a bit) nerdy team that loves to move fast!
Average salary estimate
If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.
PhD-level Statistics Intern to join AbbVie’s Stats team at the North Chicago campus to perform research, develop statistical methods, and present results to department leadership.
Lead AbbVie’s Clinical Analytics team to drive RBQM strategy and analytics innovation, delivering ML-driven insights and ensuring high-quality, compliant clinical data operations.
Lead analytics and measurement for cross-channel public affairs campaigns, managing a small data science team and applying statistical and machine learning approaches to optimize targeting and impact.
An experienced data scientist needed to lead experimentation, modeling, and product analytics at Talkiatry to surface actionable insights and guide strategic product decisions.
AbbVie is hiring a Senior Manager in Statistical Innovation to lead advanced modeling, simulation, and novel statistical and machine learning methods for clinical development.
Experienced ML engineer wanted to lead production-grade healthcare ML projects, span the full ML lifecycle, and mentor a growing data science organization in a remote US role.
Remote Data Scientist (US/Canada) to build predictive models, run experiments, and deliver data-driven insights that shape product and business decisions.
Senior Data Science Engineer needed to develop and productionize ML solutions on healthcare-scale data while providing technical leadership and mentoring across the data science organization.
BHG Financial is hiring a Quantitative Analyst II to apply statistical modeling, data analysis, and visualization to improve lending decisions and drive measurable business impact in a fast-growing financial services environment.
Gecko Robotics is seeking an experienced Machine Learning Engineer to develop, research, and productionize ML models that interpret complex sensor data for infrastructure inspection and prognostics.
Data Scientist (Watchlist) at Socure — design, build, and productionize machine learning models and analytics to detect identity fraud and improve risk decisions across large-scale data.
Lead measurement and experimentation as Quizlet’s Principal Marketing Data Scientist to drive top-of-funnel growth through incrementality, MMM, and actionable budget allocation.
Work remotely as a Machine Learning Engineer building and deploying LLM-driven automation and analytics features while collaborating with engineering teams to ensure scalable, secure, and low-latency solutions.
Build your AI growth engine
11 jobs
🔮
Hi, I'm Risa! Your AI Career Copilot
you, just ask me below!
