Data Strategist

Working at Thinking Machines

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.

Role Description

We are a data science consultancy seeking a full-time employee to join our Data Strategy team. We are a small, but high-performance team of data scientists, designers, and engineers. You'll have a huge pool of talent to learn from, all within arm’s reach!

As part of the Data Strategy team, you will be instrumental in the analysis of client requirements as well as in the implementation of Thinking Machines’ solutions. We help clients navigate the complex landscape of big data and machine learning techniques to determine the best strategies to achieve their business objectives. You’ll be in constant contact with potential clients, current clients, government agencies, and fellow data firms in the tech sector.

Your main challenge is to understand the client’s business processes, identify critical data, and customize our data science offerings to their context. Some of your initial projects will involve gathering client information and requirements, analyzing data, developing proposals, and communicating recommendations.

In addition to working directly with clients, you will collaborate with Thinking Machines colleagues to develop a broad range of business development resources. We encourage you to explore different functions of data science (e.g. engineering, machine learning, storytelling). As you intersect with elements of their specialty, you will be well-positioned to draft case studies, blog posts, white papers, and other externally-oriented materials that advances the practice of Thinking Machines across government, industry, and the social sector.

On a typical day, you might be scoping out new projects with one of our clients, working on a product spec document for our internal projects, building out a profitability spreadsheet model for a new business opportunity, answering interview questions on data science for social good for PR briefing, and compiling speaking notes for a Senate hearing on AI for our CEO.

You'll also be expected to help out on any tasks that may come up in any department. Since the startup space can get crazy, we are looking for someone who is up for any kind of challenge and has the initiative to seek out ways to be useful. We move fast, and we expect you to keep up!

Requirements

We’re looking for someone who meets the following profile:

Qualifications and Competencies

Huge Plus for people who:

Benefits and Perks

We offer the following compensation and benefits:

How to Apply

If you fit this profile and we sound like the kind of people you want to work with, fill up the form below with your information and resume. After submitting the form, please expect an email from us within the next 15 minutes, detailing the next steps for your application. If you do not receive an email from us, please contact [email protected]

STORIES

Can machine learning and satellite imagery help improve humanitarian aid to Venezuelan migrants?

A hard life awaits millions of Venezuelan migrants seeking refuge in neighboring Colombia.

Querying Safely in the (Google) Cloud

Programming in BigQuery may feel very light, but do you have a safety net for when the cloud goes down?

What’s the story? How we taught a deep learning model to understand the topics in thousands of online articles

We built a deep learning word embeddings model that learns nuanced topic relationships by reading the news.