Machine Learning and Data Science Internship

We recruit our entry-level members through our full-time internship program in Helsinki. Internships are in three months, during which you are able to improve your machine learning skills and work in our client projects.

This time, we have a paid three-month intern machine learning developer position, starting as soon as possible. As a new member, you will be part of the development team responsible for developing machine learning applications. After a successful internship, you have a chance to have a full-time job contract.

Qualifications

• You are able to learn new knowledge and to master your new skills quickly.
• You are a good team player, who is able to help the team to find out the best solutions to the problems.
• Familiar with Agile developments.
• Background in a quantitative field, e.g., Computer Science, Physics, Mathematics, Statistics, Engineering.
• Understanding of machine learning concepts and algorithms, both theory and practice.
• Good in Python language, experienced in Python frameworks such as Django or Flask.
• Good in R, knowledge of R shiny is a plus.
• Good at databases, RESTful API, Authentication, Authorization.
• Good at Linux environments.
• Able to setup servers in cloud platforms: AWS, Digital Ocean …

Machine Learning Scientist

Top Data Science is hiring a full-time machine learning scientist, initially for a 6 month project with a possibility of joining the team further on permanently.

Key Responsibilities

• Dig in (explore and visualize) client data (image, text, time series…) to gain an overall understanding of the problem.
• Design several machine learning approaches to tackle the problem. Compare and validate those in a scientific manner, having an opinion on what is good-enough for business value.
• Implement the decided solution as well as the software infrastructure to enable a production-ready output.
• Transfer, communicate and report the gained knowledge and key findings out of the analysis, internally and externally.

Qualifications

• “Have fun and enjoy the game” attitude.
• Background in a quantitative field, e.g., Computer Science, Physics, Mathematics, Statistics, Engineering.
• Understanding of machine learning concepts and algorithms, both theory and practice.
• Proficient in Python (R is a plus), familiarity with numpy, scipy, TensorFlow, scikit-learn, pandas, nltk.
• Hands-on experience with deep learning concepts and architectures.
• Scientific mindset.
• Familiarity with Linux command line, scripting and automation.
• Excellent communications skills, spoken and written, in English.
• Team player, ability and experience to work in a multicultural setting.