Director, Business Operations [Solo Quedan 15h]...

Factored was conceived in Palo Alto, California by Andrew Ng and a team of highly experienced AI researchers, educators, and engineers to help address the significant shortage of qualified AI & Machine-Learning engineers globally. We know that exceptional technical aptitude, intelligence, communication skills, and passion are equally distributed around the world, and we are very committed to testing, vetting, and nurturing the most talented engineers for our program and on behalf of our clients.

As we scale, we’re looking for a Director of Business Operations. The ideal candidate is a strategic and execution-driven leader who can act as the operational backbone of the company, ensuring alignment, efficiency, and measurable impact across all areas of the business. You will oversee and optimize Factored’s core operations across Talent Operations and Client Success while driving cross-functional alignment and operational excellence throughout the organization. This role blends strategic leadership and hands‑on execution : you’ll diagnose business challenges, design scalable solutions and participate in the implementation.

What you will be doing :

Operational Leadership & Strategy

• Design, implement, and continuously improve Factored’s operating model to ensure agility, scalability, and alignment with business goals.
• Define key metrics, dashboards, and OKRs to measure operational performance and drive data‑informed decision‑making.
• Translate strategic goals into actionable plans that optimize workflows, systems, and accountability across teams.
• Partner closely with the VP of Operations and the leadership team to drive cross‑functional initiatives that improve efficiency, profitability, and customer satisfaction.

Cross‑Functional Efficiency & Problem Solving

Talent Operations

Client Success & Delivery

What You Bring to Factored

At Factored, we believe that passionate, smart people expect honesty and transparency, as well as the freedom to do the best work of their lives while learning and growing as much as possible. Great people enjoy working with other passionate, smart people, so we believe in hiring right, and are very selective about who joins our team. Once we hire you, we will invest in you and support your career and professional growth in many meaningful ways. We hire people who are supremely intelligent and talented, but we recognize that intelligence is not enough. Perhaps more importantly, we look for those who are also passionate about our mission and are honest, diligent, collaborative, kind to others, and fun to be around. Life is too short to work with people who don’t inspire you. We are a transparent workplace, where EVERYBODY has a voice in building OUR company, and where learning and growth are available to everyone based on their merits, not just on stamps on their resume. As impressive as some of the stamps on our resumes are, we recognize that human talent and passion exist everywhere, and come from many backgrounds, so stamps matter much less than results. All of us are dedicated doers and are highly energetic, focusing vehemently on execution because we know that the best learning happens by doing. We recognize that we are creating OUR COMPANY TOGETHER, which is not only a high‑performing fast‑growing business but is changing the way the world perceives the quality of technical talent in Latin America. We are fueled by the great positive impact we are making in the places where we do business and are committed to accelerating careers and investing in hundreds (and hopefully thousands) of highly talented data science engineers and data analysts. In short, our business is about people, so we hire the best people and invest as much as possible in making them fall in love with their work, their learning, and their mission. When not nerding out on data science, we love to make music together, play sports, play games, dance salsa, cook delicious food, brew the best coffee, throw the best parties, and generally have a great time with each other.

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