Join the BPX Machine Learning Challenge:

Optimizing ESP Pump Reliability Through Predictive Analytics of ESP Run Life

Date: March 8th through April 1st

Dive into a real-world problem that combines technology with crucial predictive maintenance efforts! This Machine Learning Challenge tasks you with the early detection of Electric Submersible Pump (ESP) failures, using authentic field data. The dataset includes detailed time-series and retrospective diagnostic data, offering a solid foundation for your analysis and model development.

Your goal? To construct a robust model capable of identifying signs of ESP failures at least 30 days in advance. This challenge not only tests your ability to work with complex datasets but also your skill in creating predictive models that can significantly impact operational efficiency and maintenance strategies. The evaluation of your model will be based on its performance on a blind test dataset, measured by the F1 score metric.This challenge is an exceptional opportunity to apply your data science skills to a meaningful problem, enhancing your expertise and contributing to advancements in predictive maintenance techniques.

Amazing rewards are up for grabs! We're not just talking about bragging rights; the top 3 teams will walk away with cash prizes:

$500 for 1st place,

$300 for 2nd place &

$200 for 3rd place!

And there's more for the champions! The first-place winners will not only receive the top cash prize but also unlock exclusive opportunities for interviews with BPX. This is your chance to potentially elevate your career in one of the leading companies at the forefront of technology and innovation.

So, gear up to showcase your skills, solve real-world challenges, and possibly transform your career trajectory. It's more than a competition; it's a chance to make your mark, gain recognition, and open doors to new possibilities.

Are you ready to rise to the occasion and claim the prizes that await?