Engineering Manager - Data Science (AdTech)
About The Position
Fluent is building the next-generation advertising network, Partner Monetize & Advertiser Acquisition. Our vision is to build an ML/AI-first network of advertisers and publishers to achieve a common objective — elevating relevancy in E-commerce for everyday shoppers. As our Engineering Manager - Data Science, you will lead the team responsible for driving business value through machine learning and advanced analytics. You will own ROAS optimization, audience propensity modeling, and ML-powered capabilities that differentiate Fluent's advertising products and drive client success. This role combines hands-on ML expertise with people leadership, requiring you to set technical direction for modeling initiatives while building and developing a high-performing data science team. This role is fully remote in the United States or Canada (Ontario), with occasional travel to NYC.
Requirements
- 5+ years of experience in Data Science or ML Engineering, with at least 2 years managing or leading teams.
- Strong ML fundamentals: classification, regression, clustering, and production ML deployment.
- Experience with audience/customer modeling: propensity, lookalike, segmentation, or recommender systems.
- Production ML experience: not just notebooks — deploying, monitoring, and maintaining models at scale.
- Strong Python skills and experience with ML frameworks (scikit-learn, XGBoost, PyTorch, or similar).
- Proven people management skills: hiring, mentoring, and developing data science talent.
- Excellent communication skills for translating technical concepts to business stakeholders and executives.
Nice To Haves
- Ad tech, marketing tech, or performance marketing modeling experience.
- ROAS optimization and campaign performance modeling.
- Databricks and MLflow experience.
- Experience with real-time scoring and feature stores.
- Deep learning experience for NLP or computer vision applications.
- Experience with LLMs and generative AI applications.
Responsibilities
- Drive ML/AI strategy: audience propensity models, lookalike modeling, and segmentation algorithms that improve campaign performance.
- Own ROAS optimization: develop and refine models that maximize return on ad spend for clients.
- Build production ML systems: feature engineering, model training, batch/online inference, and serving infrastructure.
- Establish MLOps practices: model versioning, monitoring, drift detection, and reproducible training pipelines.
- Champion experimentation: A/B testing frameworks, statistical rigor, and data-driven decision making.
- Lead and grow the Data Science team: hiring, mentoring, performance management, and career development.
- Partner with Product and Client Success to translate business requirements into ML solutions and communicate model capabilities.
- Coordinate with Data Platform team to ensure reliable data foundations and feature pipelines for modeling.
- Translate complex ML concepts into actionable insights for business stakeholders and executives.
- Set technical direction and foster a culture of innovation, rigor, and continuous improvement.
Benefits
- Competitive compensation
- Ample career and professional growth opportunities
- New Headquarters with an open floor plan to drive collaboration
- Health, dental, and vision insurance
- Pre-tax savings plans and transit/parking programs
- 401K with competitive employer match
- Volunteer and philanthropic activities throughout the year
- Educational and social events
- The amazing opportunity to work for a high-flying performance marketing company!
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What This Job Offers
Job Type
Full-time
Career Level
Manager
Education Level
No Education Listed
