thinkers needed

We’re looking for problem solvers with a passion for data.
Be part of a dynamic data science startup that’s results-oriented,
civic-minded, and invests in the growth of every person on the team.

Thinking Machines is a data science startup. Our vision is for the Philippines to become a global hub for data science. To do that, we create data science cultures, one organization at a time.

We’re a company made up of intellectually curious, civic-minded, forever-learning individuals. We believe that great data science products are built with care for people, and that the best way to drive inclusive innovation is to start with a diverse team.

Our field of work is incredibly dynamic, so we want to work with people who are committed to growing with us. We want to hire people who can demonstrate an ability to learn, then provide them with personalized coaching, growth opportunities, and a great working environment to get them to world-class.

FULL-TIME OPPORTUNITIES

Data Analyst

Be exposed to all aspects of data science and find your specialization.

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Machine Learning Researcher

Architect full machine learning products with our cross-functional teams.

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Data Engineer

Collect, store, and guard the lifeblood of our organization—data.

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Data Strategist

Formulate, pitch, and execute data-driven business decisions.

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Data Visualization Developer

Turn complex data into convincing stories and cool visualizations.

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Operations Associate

Support the company's operations as we enter hypergrowth

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STORIES

Huge areas of PHL are still missing from OpenStreetMap, satellite data reveals

There are still a lot of uncharted territories in the Philippines, at least on OpenStreetMap, the world's Wikipedia of Maps. #MapTheGap

Using AI for Automatic Logo Detection on Store Shelves

We rapidly developed a high-performance logo detection model and front-end mobile application that identified our client’s product on retail shelves.

Zero in on the Philippines’ most vulnerable communities – with the click of a mouse

Estimate wealth and poverty for any 18 square kilometer area within a fraction of the time and cost of running a household survey.