At the SEAT:CODE we are constantly looking for talented people willing to join our projects. Our start-up environment is very open-minded, we love to test and implement new ideas. If you think you are ready to enjoy your work and be part of our big family, we invite you to keep reading what we think it could be a good fit for our current needs. We are looking for a full-time DATA Scientist. You will work on a day-to-day basis in squads with talented designers, product owners & software developers to build a scalable and solid product.

The Data Scientist role:

These extravagant competencies are particularly distinctive:
Above average team ability.
Above-average learning readiness.
To rethink the team’s feedback to reflect within the framework of the Balanced Team Approach (Janice Fraser).
High degree of self-interest.
High analytical competence.




2+ years’ experience in data science/quantitative analysis.
Understanding of statical analysis. Excellent data mining skills.
Expertise in predictive analytics, artificial intelligence, machine learning: supervised learning, clustering, and time series analysis.
Experience working with multiple data-sets.
Has an eye for data visualisation and can demonstrate creativity.
Excellent problem-solving skills and proven technical leadership.
Programming experience in Python and/or with Java/Kotlin/R is a plus.
Experience with Data Science and Machine Learning platforms like DataIKU, Alteryx or Knime.
Experience with all AWS Data related services (Athena, S3, Glue, API GW, kinesis, etc..) is a plus.
Ability to extract business metrics/questions from data sets.
Ability to turn vague concepts and asks into well-documented and effective business metrics and insights.
Excellent written and verbal communication skills including the ability to identify and communicate data-driven insights in a clear and effective manner.
Bonus: experience in relevant vertical industries: consumer electronics, automotive, industrial, health.
Fluent in English and Spanish

Language requirements:

Fluent in English and Spanish.

Level of experience (years):

Mid Career (2+ years of experience)

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