Beat is one of the most exciting companies to ever come out of the ride-hailing space. One city at a time, all across the globe we make transportation affordable, convenient, and safe for everyone. We also help hundreds of thousands of people earn extra income as drivers.
Today we are the fastest-growing ride-hailing service in Latin America. But serving millions of rides every day pales in comparison to what lies ahead. Our plans for expansion are limitless. Our stellar engineering team operates across a number of European capitals where, right now, some of the world’s most ambitious and talented engineers are changing how cities will move in the future.
Beat is currently available in Greece, Peru, Chile, Colombia, Mexico and Argentina.
Working on Machine Learning at Beat, means you will work on high impact use cases across the domains of dynamic pricing, fraud detection, and dynamic dispatch with a strong focus on systems for making real-time decisions.
At Beat we do Machine Learning and Data Science with a product engineering mindset. In our Machine Learning chapter, you work with your colleagues in cross functional teams to translate product features into predictive modelling and machine learning problems. Exploratory analysis and hypothesis testing using the tools provided by Beat’s Big Data capabilities team help you build a deep understanding of the behaviour of our millions of daily users. You showcase how your models drive product features through rapid prototyping.
Then comes the best part: taking it to production. You care deeply about scalability and performance of training and inference. You work with other teams to productionise and monitor pipelines and setup telemetry data collection required to monitor your model in production. This way, you take on full ownership of your models running in production.
You are curious by nature, challenge assumptions, and naturally explore domain knowledge before jumping into solutions. You care about the real world context behind the data. As a strong communicator with business acumen you explain the essence of your modelling approach in business terms to product managers, designers, engineers, and other colleagues, while considering the implications of your solutions on Beat’s mission and bottom line.
You use your programming skills to automate workflows, build reproducible analyses, and deliver prototypes. Your tools of choice might include Python or R, as well as distributed computing on a Spark cluster, or running SQL queries against large datasets. Ideally, you are not afraid to dive into options like Scala for a high performance Spark job or perhaps Golang for a production service.
You can rigorously defend the maths and statistics behind your results and you have a working knowledge of the landscape of machine learning models and approaches, understanding their underpinning assumptions and implementation caveats.
You know that the life of a model only begins when it runs in production. You have a passion for the software engineering work behind computational performance, software architecture, and production monitoring of predictions and residuals. You continuously build the best experience for users whose day to day is affected by your prediction outcomes.
This job is for you if you:
This job is not for you if you:
Please note that you will be working as contractor.
You are only one step away from being able to work remotely from anywhere. Fill out your email address here and then you will be directed to the application page for this remote job position. Good luck!