• Anywhere

Working at Thinking Machines

Thinking Machines is a technology consultancy building AI & data platforms to solve high-impact problems for our clients. Our vision is for the Philippines to become a global hub for data science. To do that, we create data cultures, one organization at a time.

We’re a company composed of intellectually curious, civic-minded, forever-learning individuals. We believe great data science products are built with care for people and 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

This intern position is a great opportunity for Filipino college students looking for an immersive internship or fresh graduates and career shifters just starting in the data science industry. Build your skills in data engineering, solutions engineering, software engineering, quality assurance testing, analytics engineering, or data operations engineering.

This year, we’re looking for interns who are ready to learn, get hands-on experience, receive mentorship from a member of our team , and work at a fully remote setup. We will match your background and skills to one of the following teams you can potentially become a part of:

Work on cloud platforms and data orchestration tools with our Data Engineering Team

Design data and cloud architectures with effective sales strategy with our Enterprise Solutions Team

Develop web apps using the latest frameworks and technologies with our Software Engineering Team

Test software applications to ensure its quality and reliability with our Quality Assurance Testing Team

Contribute to improving data observability and quality checks in data pipeline projects with Analytics Engineering Team

Work on projects involving data scheduling, ETL pipelines, and data warehousing with our Data Operations Engineering Team

We’re looking for individuals who:

Are university students (3rd year and above) or fresh graduates (batch 2024) from courses such as Management/Management Engineering, Business Administration, Marketing, Information Design, Environmental Science, Decision Science or similar fields
Are career shifters from other fields and new to data science and tech consultancy
Can commit to a full-time (40 hours per week), fully-paid, and remote-first internship for 10 weeks
Can show a track record of being able to work hard, solve problems, learn independently, do quality work, and communicate effectively
Can strongly demonstrate skill depth in some areas (e.g. creating great slide decks, building web apps, great at algorithmic coding competitions, respectable rank on Kaggle, etc.)
A personal machine or laptop and a stable internet connection

Qualifications

This intern track is for you if you have any (but not necessarily all) of the following skills:

Python
Git
SQL
Software or Web Development
Familiarity with basic code languages (HTML, CSS, Javascript)
Working knowledge of cloud technologies (i.e., GCP or AWS)
Familiarity with CLI commands (Linux, Windows)
Working knowledge of different testing types (e.g. functional, non-functional, regression)
Basic understanding of test cases and test scenarios
Presentation Skills
Research
Team Collaboration

Bonus Points if you have experience in the following:

Cloud technologies (i.e., GCP, AWS)
Familiarity with API
Basic understanding of test automation
Familiarity with Infrastructure and networking
Familiarity with Data analysis, Data Governance, and Machine Learning
Strong presentation skills (experience participating in public speaking, content writing, or case study competitions)

Logistics

10 weeks starting June 10, 2024
Paid internship

Full-time, remote-first work

Send in your resume and fill out the form below to kickstart your application!

Deadline of Application is on April 5, 2024, 11:59 PM.

Originally posted on Himalayas

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