Fluent, LLC

AdTech

EngineeringManager,DataScience(AdTech)

CA$180–225k Toronto, Ontario, Canada; New York City, New York, United States FULL TIME Remote Friendly
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Manager candidates.

The Brief

“Engineering Manager, Data Science (AdTech) at Fluent, LLC. Skills: Deep Learning, Agentic AI, MLOps, People Leadership. Drive Deep Learning Evolution. Own Value-Based Bidding”

What You'll Achieve.

driving business value through machine learning; elevating relevancy in E-commerce; ROAS optimization; audience propensity modeling; deep learning powered capabilities; differentiate Fluent's advertising products; drive client success; maximize client returns; enhance decisioning and operational efficiency; optimize directly for business outcomes

Industry & Context.

AdTech
Problems you'll solve

solve for data sparsity; long-term user value; optimize directly for business outcomes

Eligibility Requirements

occasional travel to NYC

What They're Looking For.

Must Have

Master’s Degree in Computer Science, Mathematics, or other Quantitative Field, 8+ years of experience in Data Science or ML Engineering, 2 years managing or leading technical teams, Deep hands-on experience with modern ranking and retrieval architectures, Experience deploying complex models into high-throughput, low-latency production environments, Python skills with a focus on Deep Learning frameworks, Proven people management skills, Excellent communication skills

Nice to Have

PhD, Hands-on Agentic Framework Experience, ROAS optimization and campaign performance modeling, Databricks and MLflow experience, Experience with audience/customer modeling

What You'll Do.

Drive Deep Learning Evolution

Own Value-Based Bidding

Champion Agentic AI & Automation

Build Production Deep Learning Systems

Advance MLOps & Experimentation

Lead and grow Data Science team

Partner with Product and Client Success

Coordinate with Data Platform team

Translate complex ML concepts

Set technical direction

How You'll Work.

Team & Collaboration

Partner with Product and Client Success; Coordinate with Data Platform team; Translate complex ML concepts to business stakeholders; Set technical direction and foster innovation; hiring, mentoring, performance management, career development

Communication Scope

Excellent communication skills for translating technical concepts to business stakeholders and executives

Full Job Description

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 in the Adtech space. You will own ROAS optimization, audience propensity modeling, and deep learning powered capabilities that differentiate Fluent's advertising products and drive client success. We are seeking expert-level knowledge of sequence modeling (Transformers/Attention) and generative approaches for user behavior, moving beyond legacy logistic regression to implement deep architectures that solve for data sparsity and long-term user value. 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 Ontario, Canada, with occasional travel to NYC. ### **What You'll Do** _**Machine Learning & Modeling**_ * Drive the Deep Learning Evolution: Lead the architectural transition from legacy tree-based models (XGBoost) to advanced Neural Network architectures (Deep Learning) for audience propensity, lookalike modeling, and real-time segmentation. * Own Value-Based Bidding (ROAS): Evolve our bidding strategy from simple conversion prediction to sophisticated ROAS-based optimization, developing models that predict user value (LTV) to maximize client returns within dynamic auction environments. * Champion Agentic AI & Automation: Spearhead the exploration and adoption of autonomous agentic workflows to enhance decisioning and operational efficiency, moving beyond static models to self-correcting systems. * Build Production Deep Learning Systems: Oversee the end-to-end engineering of high-scal

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