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Director, Data Science & AI

Full-time

Trusted Media Brands

About Us:

TMB is the community-driven entertainment company engaging more than 250 million consumers worldwide across streaming TV, social media, web, and print. Our portfolio of brands including FailArmy , Family Handyman , People Are Awesome , Reader's Digest , Taste of Home , The Healthy , and The Pet Collective , is powered by content that's inspired and created by our fans. Together our community sparks curiosity, fuels laughter, and inspires people to live big, full, fantastic lives. Learn more about our brands, our data-driven marketing solutions, our award-winning licensing services, and much more at trustedmediabrands.com .

Location:

We have offices in New York, Los Angeles, Milwaukee, and Gurgaon. This position will be based in the United States and can work remotely.

About the role:

TMB is looking for a Director of Data Science & AI to lead the team and efforts to turn data into decisions, deliver scalable intelligence that drives personalized experiences and business outcomes, and lean into AI and Automation where it makes sense. You understand how business users think, what friction looks like in real workflows, and how to communicate technical solutions in ways that land with non-technical users.

Your primary mission is to bridge the gap between what’s technically possible and what’s practically useful. This is a hands-on leadership role: you’ll set the technical direction, but you’ll also be in the data, in the model reviews, and building alongside your team when it counts. We need someone fluent in Google Cloud Platform (BigQuery, Vertex AI, and broader GCP ecosystem), has strong data science capabilities and the grit to take ideas from research to production.

You are a fast learner who is comfortable in ambiguity, energized by solutioning, and motivated by seeing your work drive real adoption across the organization. You'll spend your time championing smarter ways of working and helping both technical and non-technical teammates integrate AI into their everyday work, not as a disruption, but as a natural extension of how they already operate.

Your day-day: (aka Responsibilities)
  • Own the data science roadmap for the organization from core statistical modeling and experimentation forecasting, segmentation and applied AI where it adds real business value
  • Lead, mentor, and stay hands-on with a small team of data scientists: writing code and reviewing methodology, not just roadmaps
  • Oversee the design of robust, production-grade solutions utilizing core cloud systems, vector databases, and agentic workflows
  • Champion the adoption and continuous improvement of AI development tools across technical teams
  • Scale MLOps/LLMOPs practices, ensuring data observability, governance, model safety, and ethical AI compliance
  • Collaborate cross-functionally with Business Intelligence, Data Engineering, Analytics Engineering, Development, and Product teams to drive technical innovation, prioritize initiatives, ship MVPs fast and iterate based on usage data
  • Design and run rigorous experiments to validate hypotheses and guide business decisions
  • Translate statistical and technical work into business language for executive stakeholders and make the case for where data science investment should go next
  • Define success metrics for internal tools and AI initiatives, and track adoption, usage, and business impact over time
  • Document tools, workflows, and best practices to scale impact beyond individual engagements
  • Stay informed on industry trends, viral content, and emerging platforms to identify new opportunities
You have: (aka Qualifications)
  • 7+ years in data science, including leading or managing a technical team
  • Strong foundation in core data science
  • Deep, hands-on fluency in Google Cloud Platform: BigQuery, Vertex AI, and building/deploying production models in a GCP environment
  • Proficiency deploying custom Gemini Enterprise Agents via Agent Engine
  • Fluency in AI tools such as Claude, CoPilot and ChatGPT
  • Strong Python and SQL skills and experience in applied AI
  • A bias for action
About this team:

The Data Science team is a small but mighty group sitting at the center of the organization. We're a centralized team, which means we work across nearly every department: from Marketing and Creative to BI, Engineering, Product, and beyond. If there's a workflow to improve, a tool to build, or a data problem worth solving, chances are we're involved.

Our work is practical by design. We build internal tools and data products that make real work easier, not to chase trends, but because the right solution at the right moment can meaningfully change how an entire team operates. We use AI where it genuinely helps, and we're skeptical of hype for its own sake. That pragmatic instinct is part of what makes us effective.

As a team, we move fast and stay scrappy. We're not a big org with lengthy approval chains. We prototype, iterate, and ship. We collaborate constantly, both within the team and across the business, and we're at our best when we're working alongside stakeholders to understand their problems firsthand rather than solving in a vacuum.

If you're joining us, you're joining a team that values curiosity, initiative, and craft. Our team genuinely believes the most impactful data work happens when technical depth meets real business context.

Our Benefits:

We value our people and offer a collaborative and engaging culture. As a Trusted Media Brands employee, you will enjoy work/life balance, generous time off and comprehensive benefits and programs. Learn more about what life is like working at Trusted Media Brands at .

Trusted Media Brands embraces inclusivity and values our diverse community. We are committed to building a team based on qualifications, merit and business need. We are proud to be an equal opportunity employer and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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Vacancy posted a month ago
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