As a Data Scientist, you will leverage your statistical analysis and machine learning expertise to develop predictive maintenance models. You will collect and preprocess relevant data, build, train, and productize machine learning models, and collaborate with cross-functional teams to translate them into product features and actionable recommendations. Your ability to understand complex data patterns, extract meaningful insights, and communicate findings effectively will be vital for the success of our predictive maintenance initiatives.
You will be part of our AI team, which creates robust and innovative solutions that increase the value, efficiency and reliability of our AI based predictive analytics.
Bonus Points
According to our internal progression framework, these are some of our expectations for this role:
References may be required at any stage of the recruitment process.
Stratio is the World’s Leading Real-time Predictive Fleet Maintenance Platform. The company's proprietary technology combines large-scale processing with the latest machine learning techniques to prevent hundreds of thousands of breakdowns from happening every day, thus saving millions of people from the hassle of public transportation delays, postponed deliveries, or late arrival of essential goods.
Stratio’s platform enables zero downtime for 5 of the 10 largest transportation companies in the world and, in 2021, raised an investment of $12 million to boost leadership in predictive fleet maintenance. Fleet operators in Europe, North America, Asia-pacific, and Latin America trust Stratio’s technology to fully leverage the data under the hood to safeguard operations, and keep customers happy. Stratio’s technology has enabled transportation for 1.3 billion people so far.
We want inspiring individuals in our teams, where age, race, gender, sexual orientation, politics and religion do not matter, and seek to create a tolerant and open space for everyone. We thrive to provide an inclusive and trustworthy environment.
You can find our Culture Manifesto and more team information here.
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