Canva
2020 Data Science Summer Internship
Opportunity expired
Opportunity details
- Internship, Clerkship or Placement
- Apply by 17 Jun 2020
Since launch in April 2013, we have grown exponentially, amassing over 10 million users in over 100 languages, making us one of the world's fastest-growing technology companies. We're growing rapidly and building a product that users really love.
As a Data Science Intern, you will have the opportunity to learn from Data Scientists and Engineers from the likes of Google, JetBrains, Yandex, Atlassian, Amazon, Facebook, and popular technology houses from all over the world.
You will get the opportunity to learn and apply best-practice data science and software engineering, focused on strong software engineering fundamentals and pragmatism.
You will have the opportunity to do meaningful work and build features and functionality that impacts millions of users around the world.
The Data Science specialty is highly engaged in delivering value to Canva's users, by designing, building and maintaining complex systems to apply statistics and machine learning at scale. This includes making it easy for users to search over 50 million images for design, recommending design styles, and making it easier to design what they need.
What to look forward to:
- Work alongside data analysts and engineers, software engineers, product owners – to identify business and growth opportunities.
- Improve scalability, speed and performance of existing models
- Conceptual modelling: share and articulate modelling
- Statistical analysis: understand and work around possible limitations in models
- Predictive modelling: most of the big data problems are towards being able to predict future outcomes
- Hypothesis testing: develop hypotheses and test them with careful experiments
This will be perfect for you if:
- Are currently within 12-18 months of completing a Bachelor's or Master's degree, or at any stage in your PhD.
- Are comfortable working in Python, Scala or Java.
- Have strong Computing Fundamentals.
- Have the ability to conceive and translate quantitative models (statistical models) to practical, scalable solutions.
We'd love it if you have:
- Experience with data platforms (e.g. Spark and Hadoop).
- Experience with machine learning frameworks (e.g. Scikit learn, TensorFlow).
- Experience with interactive notebooks for exploration of data and initial prototyping.
Requirement:
- Please provide us with the latest PDF copies of your CV and grades/transcripts by compressing them into a zip file on our careers page.
Reviews
Love 85-90% of the work I get to do. 10-15% less enjoyable bureaucracy / 'keeping the lights on' work that is required.
As a backend engineer, I mainly work closely with maintaining the server, including the interaction with the database and cache. I also apply software development techniques when writing code.
I am currently working as an Associate Machine Learning Engineer. My responsibility includes maintaining existing deployed ML models in Canva and developing new ones to help users get a better experience. Sometimes it involves some data analysis as well as research.
About the employer
Canva
4.7
1,000 - 50,000 employees
Technology
Canva is a global online visual communications platform designed to empower the world to design.
Pros and cons of working at Canva
Pros
The culture and work-life balance at Canva is amazing! It helps me unlock my full working potential as I am encouraged to work at my own pace and to the best of my comfort.
Work hours are flexible as you can work at your own pace which boosts your efficiency the most. You can work fully remotely or in the office depending on your choice.
I get to work with very talented people and solve interesting problems at scale.
Free food, club activities, and events can sometimes seem too good to be true. Additionally, the company is flexible and trusting of different working schedules.
The company is extremely committed to diversity.
Cons
If you live in an area that does not have a hub or office, there will be less interaction unless you go to the office. This makes it hard for people to network and meet up regularly.
Working at a large company often means you specialise in a narrow set of tools, which can limit your exposure compared to working at a smaller startup.
Can be a fast-paced, stressful environment when launches are approaching.
Currently, I think my daily job involves much busy work without much time to understand the context.
Being remote first, although this is another really great benefit, I sometimes wish I could see my teammates more in person.