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Machine Learning Specialist
Are you passionate about Machine Learning, Data Mining and Predictive Analytics?
Want to be part of a team of multicultural experts?
This is your opportunity to be part of a new and innovative copper exploration initiative in Chile. The company is part of a
major business group established in London. It is focused on discovering mineral deposits while significantly improving
exploration, maximizing chances of success and minimizing chances of failure.
Job description (Key Accountabilities)
Support the Data Science team, drawing on theoretical knowledge and prior technical experience pertaining to
machine learning, predictive analytics, data mining and statistics.
Develop and maintain the Data Science infrastructure:
Conduct preliminary data exploration and data preparation steps. Perform variable/algorithm selection,
model development and validation, metrics definition and scoring/ranking.
Maintaining hardware, software and data base infrastructure.
Responsible for presenting analysis, methods and results to non-expert personnel, management team and technical
experts throughout different projects.
Interact with the global academic and business community to develop new techniques
Required Experience
 Master or PhD in applied computational mathematics, computer science, engineering or similar quantitative field
 5+ years of relevant experience in Data Mining / Statistical Analytics/Predictive Analytics/Machine Learning
 Experience with data driven projects from definition through execution and interpretation
 Knowledge and scripting experience in Matlab and Python
 Skills in programming languages like C
 Advanced level of English
It’s important when applying for the position, to indicate:
Degree and institution in which you studied, mention if you have a Master or PhD
If you have fulfilled a similar position or role in your career
Years of experience in Machine Learning/Data Mining
Which programming language(s) you are used to work with
Monthly net income expectations
If you´re interested contact us by sending your CV to our Human Resources Dept.: [email protected]