StackAdapt

Boston
Total Offices: 4
371 Total Employees
Year Founded: 2013

StackAdapt Benefits Overview

Compensation + Benefits

Offers 401(K)

Offers life insurance

Offers dental insurance

Offers health insurance

Offers mental health benefits

Offers Flexible Spending Account (FSA)

Offers vision insurance

Offers generous parental leave

Work-Life Balance + Wellbeing

Offers company-sponsored outings

Offers generous PTO

Provides paid holidays

Offers paid volunteer time

Provides paid sick days

Career Growth + Development

Provides customized development tracks

Company Culture

Offers a remote work program

Provides free snacks and drinks

Provides a mobile phone discount

Offers diversity-based Employee Resource Groups

Recently posted jobs

One Month AgoSaved
In-Office or Remote
Chicago, IL, USA
AdTech • Marketing Tech
Manage post-sales relationships for a portfolio of advertising clients, driving platform adoption, campaign success, retention, and account expansion. Develop programmatic campaign strategies, traffic and optimize campaigns, implement tags and pixels, analyze performance, provide reporting and strategic recommendations, and lead client meetings, presentations, business reviews, and training. The role requires strong RTB and DSP expertise and includes travel up to 20%.
2 Days AgoSaved
Remote
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AdTech • Marketing Tech
Drive new and existing revenue for StackAdapt’s programmatic advertising platform by identifying and closing sales with agencies and brands. Manage client relationships, develop account growth opportunities, present campaign strategies, build pitch decks, maintain CRM pipelines, and communicate platform capabilities. Collaborate with account managers, management, and product teams to support client retention, renewals, and product adoption. Occasional regional travel is required.
4 Days AgoSaved
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2 Locations
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Lead the development, optimization, and production deployment of advanced machine learning algorithms for advertising effectiveness and ROI. Build scalable ML models, write efficient code, collaborate with machine learning engineers, prototype and test algorithms and data pipelines, and drive iterative improvements using historical data and rigorous performance analysis.