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Seeking a forward deployed Data Scientist to join our cross-functional Data Science team. This role is uniquely positioned at the intersection of media analytics, product innovation, and applied machine learning. You will work directly with high -value clients and internal stakeholders to extract insights from media performance, recommend improvements to DS/ML infrastructure, and actively configure and deploy models across new or evolving use cases. This is not a traditional analytics position—ideal candidates will thrive in ambiguity, prototype quickly, and contribute to core data science products by bridging product - market context with modeling expertise.

Key Responsibilities:

Client-Facing Media Analytics & Strategy

• Serve as the embedded data science expert across client teams to analyze media performance, model performance, and recommend and/or prototype improvements.
• Translate raw data, model logs, and client KPIs into actionable media recommendations.
• Conduct lift analyses, segment-level attribution, and targeting strategy refinement.

Core Model Configuration & Deployment

• Build and adapt MLE and DS configurations for existing modeling products (e.g., audience scoring, incremental lift, bid modifiers).
• Configure pipelines, stratified sampling logic, or feature transformations tailored to client-specific challenges.
• Work closely with engineers and product managers to productionize prototypes into scalable tools.

Product Feedback & Internal Innovation

• Act as a conduit between clients and the core DS team to surface edge cases, performance drift, and new feature requests.
• Suggest improvements to model interpretability, automation, and monitoring frameworks based on field deployment.
• Participate in research and experimentation cycles around contextual targeting, identity resolution, and model evaluation.

Qualifications:

• 5+ years in data science, analytics, or machine learning roles, preferably within advertising, martech, or SaaS environments. Bachelor’s degree required, MS preferred.
• Strong grasp of causal inference, media measurement, and experimentation (e.g., geo holdouts, diff-in-diff, matched markets).
• Experience building data pipelines and models in Python (bonus for familiarity with Spark, Airflow, or MLflow).
• Ability to communicate complex technical concepts clearly to non-technical stakeholders.
• Entrepreneurial mindset with the confidence to own ambiguous, high-impact initiatives from start to finish.
• Requires working knowledge of digital ad campaign workflow and customer service

Preferred Experience

• Hands-on experience with audience modeling, bid optimization, and forecasting/simulation in the advertising industry
• Prior client-facing or agency-facing experience in a data science/analytics role.
• Exposure to advertising platform APIs (e.g., Meta, TTD, Amazon Ads) and DSP/SSP metrics.
• Familiarity with identity graphs, cross-device resolution, or hashed ID pipelines
• (RampID, UID2, etc.).

 Job-3403414

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