Job Title: Machine Learning Engineer
Location: Remote, US
Department: Data Science
Type: Full-Time, Exempt
Experience: New Grad / Early Career (0-3 Years)
Salary Range: $125,000 - $165,000 base
Core Hours: 9 AM - 1 PM PST / 12 - 4 PM EST
About tvScientific
tvScientific is the first and only CTV advertising platform purpose-built for performance marketers. We leverage massive data and cutting-edge science to automate and optimize TV advertising to drive business outcomes. Our solution combines media buying, optimization, measurement, and attribution in one, efficient platform. Our platform is built by industry leaders with a long history in programmatic advertising, digital media, and ad verification who have now purpose-built a CTV performance platform advertisers can trust to grow their business.
Role Summary
tvScientific is looking for a Machine Learning Engineer to join our growing team! You'll be working with a distributed engineering team on our Connected TV ad-buying platform, as we scale our Data Science practice. We’re building data science tools for constructing ad campaigns from content to timing to scheduling to bid optimization.
Our self-managed platform makes it easy to buy, optimize, and prove the value of TV advertising. In this role, you’ll lead small project teams, provide direction, and keep stakeholders informed. You’ll have the autonomy to determine key milestones and provide updates and check-ins to relevant teams and partners.
What You'll Do
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Culture and Benefits
At tvScientific we believe people do their best work when they feel challenged and engaged by their day to day responsibilities, when they’re surrounded by smart, hard working people, and when they have a healthy work life balance. Our company culture and benefits package reflects these beliefs.
tvScientific is committed to building an inclusive environment for people of all backgrounds and everyone is encouraged to apply. tvScientific is an Equal Opportunity Employer and does not discriminate on the basis of race, color, gender, sexual orientation, gender identity or expression, religion, disability, national origin, protected veteran status, age, or any other status protected by applicable national, federal, state, or local law.
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