Sr. Data Scientist

Insight Global • New York, NY • 1h ago

Job Description

We are seeking a Senior Data Scientist to lead Marketing Mix Modeling (MMM) and conversion/attribution analytics end-to-end. You will build the models, ship the pipelines working with Data Engineers, and work directly with Sales, Strategy & Insights, and Planning teams to turn measurement into revenue. This is not a research engagement - we need someone who has shipped MMM and statistical models to production systems, influenced real ad spend decisions, and who can hold their own in a room with both Data Scientists and Ad Sales leaders.

What You Will Do

MMM & Media Planning (~60%)

Own the MMM practice end-to-end: data pre-processing, transformation, ingestion, model development, validation, calibration, and productionalize

Collaborate with Data Engineers to build and maintain MMM pipelines on GCP that ingest spend, exposure, and outcome data across linear, ViX, audio, and digital

Translate model outputs into planning and optimization recommendations - budget allocation, channel mix, flighting, saturation curves - that Sales and Planning teams can actually use

Partner with Ad Sales tech team to integrate MMM functionality into a web app used by internal teams for audience insights, planning recommendations and campaign measurement

Calibrate MMM against incrementality tests and lift studies; reconcile MMM with MTA and platform-reported metrics

Conversion & Attribution Analytics (~30%)

Build and productionize multi-touch attribution (MTA) models that integrate with our identity graph and clean room infrastructure

Work with 1P, 2P and 3P conversion data (pixels, ACR, digital/streaming viewership, retail/sales, online search activity, etc.) to measure campaign outcomes

Execution & Stakeholder Ownership (~10%)

Ship production code. You will own the models and collaborate with the Ad Sales tech team to develop pipelines and model-serving endpoints

Independently present and defend measurement work to leadership (VP and above) and to external stakeholders including agencies and advertisers - translating model mechanics into business narratives without losing technical rigor

Work independently - this engagement requires someone with high agency and ability to take a business initiative and turn it into a productionalize measurement product

Work in a tech team - this engagement requires working with peers in the tech team, including Data Engineers, Data Scientists, Full-stack Developers, and Architects, to integrate models in end-user facing web applications.

We are a company committed to creating diverse and inclusive environments where people can bring their full, authentic selves to work every day. We are an equal opportunity/affirmative action employer that believes everyone matters. Qualified candidates will receive consideration for employment regardless of their race, color, ethnicity, religion, sex (including pregnancy), sexual orientation, gender identity and expression, marital status, national origin, ancestry, genetic factors, age, disability, protected veteran status, military or uniformed service member status, or any other status or characteristic protected by applicable laws, regulations, and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or recruiting process, please send a request to HR@insightglobal.com.To learn more about how we collect, keep, and process your private information, please review Insight Global's Workforce Privacy Policy: https://insightglobal.com/workforce-privacy-policy/.

Skills and Requirements

7+ years of applied data science experience, with at least 4 years focused on MMM and marketing/media measurement

Production ownership: you have built and shipped data pipelines and model-serving integrations - not just notebooks handed off to engineering (be ready to talk through specific systems you have put into production and the business outcomes they drove)

Strong Python/R and SQL skills; experience using modern data stack (cloud data warehouses, orchestration frameworks, version control, CI/CD)

Demonstrated experience with incrementality testing, lift studies, and MTA, including the messy parts: test design, power analysis, reconciling conflicting signals across methodologies

Experience with at least one major MMM framework, such as Meridian, PyMC, Robyn, or LightweightMMM, and can speak to the tradeoffs in going with a bespoke model versus using such frameworks

Proven ability to own stakeholder communication end-to-end: presenting to senior internal leadership (VP+), agencies, and clients without needing a layer of translation (you move swiftly between a Bayesian prior conversation and a channel-mix recommendation conversation without skipping a beat)

Able to work hybrid from our NYC office (4 days/week) Strongly Preferred:

Prior experience at a publisher, broadcaster, streaming platform, ad-tech company, or agency/measurement firm working on media-side measurement

Familiarity with ACR data, set-top box data, or digital/streaming viewership data

Experience working with 3P conversion/outcome data providers (NIQ, Polk, EDO, or similar)

Exposure to both pre-sales (research, planning, recommendation) and post-sales (outcomes, renewal) measurement workflows

GCP experience (BigQuery, Vertex AI, Composer)

Nice-to-haves:

Causal inference depth: geo-based measurement (GeoLift, CausalImpact), synthetic controls, uplift modeling

Experience with clean room environments (Snowflake, AWS, Habu, InfoSum)

Familiarity with identity resolution and cross-platform measurement

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