Fluent,

Fluent,

Fluent, Inc. is a top performance marketing company connecting advertisers to millions of consumers, enabling precise targeting and acquisition of valuable customers at scale.

Media
251-1K
Founded 2010

Description

  • Lead the Data Science team, including hiring, mentoring, performance management, and career development.
  • Own and evolve machine learning models for ROAS optimization, audience propensity, lookalike modeling, and real-time segmentation.
  • Drive the transition from legacy models to deep learning architectures for ranking, retrieval, and prediction use cases.
  • Develop user value and lifetime value models to improve bidding strategy and maximize returns in dynamic auction environments.
  • Explore and operationalize agentic AI workflows to improve decisioning and automation.
  • Oversee production deep learning systems, including inference pipelines, embedding layers, feature stores, and low-latency serving infrastructure.
  • Establish MLOps practices for model versioning, drift detection, and experimentation.
  • Collaborate with Product, Client Success, and Data Platform teams to translate requirements into ML solutions and reliable data pipelines.
  • Communicate technical concepts, model performance, and business impact to executives and other stakeholders.
  • Set technical direction and promote a culture of innovation, rigor, and continuous improvement.

Requirements

  • PhD preferred or Master’s degree in Computer Science, Mathematics, or another quantitative field.
  • 8+ years of experience in Data Science or ML Engineering.
  • At least 2 years of experience managing or leading technical teams.
  • Deep hands-on experience with modern ranking and retrieval architectures such as DLRM, DCNv2, or Two-Tower models.
  • Experience with multi-objective learning methods such as MMoE to optimize for clicks, conversions, and revenue.
  • Strong Python skills with deep learning frameworks such as PyTorch or TensorFlow.
  • Experience with traditional ML libraries such as XGBoost and scikit-learn.
  • Experience deploying complex models in high-throughput, low-latency production environments, with familiarity with ONNX, TensorRT, or feature stores.
  • Ability to connect model metrics such as AUC and LogLoss to business outcomes such as GP and RPM.
  • Proven people management and communication skills for working with technical teams and executive stakeholders.
  • Preferred: familiarity with agentic frameworks such as LangGraph, CrewAI, or Model Context Protocol (MCP).
  • Preferred: experience with ROAS optimization and campaign performance modeling.
  • Preferred: experience with Databricks and MLflow.
  • Preferred: experience with audience, customer, propensity, lookalike, segmentation, or recommender systems.

Benefits

  • Competitive compensation with a base salary range of CAD $180,000 to $225,000 plus a competitive bonus.
  • Health, dental, and vision insurance.
  • Ample career and professional growth opportunities.
  • Pre-tax savings plans and transit/parking programs.
  • 401(k) with competitive employer match.
  • Fully stocked kitchen, catered lunch, and regular office activities and events.
  • Volunteer, philanthropic, educational, and social events throughout the year.
  • Hybrid of remote work in Ontario, Canada with occasional travel to NYC.

Interested in this position?

Apply directly on the company website

Apply Now

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