Samba
Programmatic Account Manager
Los Angeles, California
Sponsorship not specified$80k-$90kDetected 42 days ago
SQLProject ManagementJiraSalesforceCRMAccount ManagementExcelSignal ProcessingCommunicationProblem Solving
About the role
- We know what the world is watching, reading, and thinking about - in real time, at scale, across every screen.
- Our data exists with the consent of over a billion people, organized into the most complete picture of consumer attention ever built.
- The biggest brands in the world use that picture to make smarter decisions.
Responsibilities
- As a Programmatic Account Manager at Samba TV, you'll manage and grow relationships with a portfolio of agency and brand partners.
- You'll ensure these partners derive maximum value from Samba's suite of audience targeting and measurement solutions.
- You'll work closely with Sales to support key accounts, drive audience activation strategies, and deliver a seamless client experience across planning, activation, and measurement workflows.
Requirements
- 3-5 years of experience in account management, client services, or programmatic strategy roles
- Strong understanding of audience activation and programmatic buying across DSPs (e.g., The Trade Desk, DV360, Yahoo DSP)
- Solid working knowledge of DMPs (e.g., LiveRamp, Lotame, Adform) and SSPs (e.g., OpenX, Magnite, Freewheel)
- CRM and project management tool proficiency (Salesforce, Jira, Asana, Trello, etc.)
- Required in office 3 days a week (Tuesday through Thursday), moving to 4 days a week (Monday through Thursday) starting January 4th, 2027, with the possibility of moving to 5 days a week in office after that.
Nice to have
- Direct experience working at or closely with agencies or brand-direct marketing teams is strongly preferred
- Background in programmatic trading or campaign management is a strong plus, even if not hands-on today
- Strong Excel skills (SUMIFS, INDEX MATCH, pivot tables, VLOOKUP)
Compensation
- $80k-$90k
This listing is sourced directly from Samba's careers page and normalized into a canonical job model.