Revolut Work from Home Jobs; Hiring Data Scientist – Apply Now

They approach Data Science at Revolut the same way that we approach everything else – with class, logical thinking, and lots of style. Let’s break it down: they take the most complex problems and create tailor-made solutions for their customers. If you’re thinking the Data team is kept in some sort of a secret den, doomed to never see the impact of their work, don’t worry - that’s not how they do things. They’re some of their best and brightest problem-solvers, deployed to the front lines to work in product teams and deliver rockstar solutions.

They start with deep data analysis to understand their customers, their objectives and any issues they might have. Revolut then use various data points and advanced machine learning algorithms, to come up with the best possible option for each client. Revolut experiment, iterate, and build fully automated solutions, based on algorithms which self-improve with time.

Name of the Organization: Revolut

Requisition ID:

Positions: Data Scientist (Credit)

Location: Remote (Work from Home)

Salary: As per company Norms

Required Skills & Qualifications:

• Experience working in a data science team of a credit institution
• A Bachelor's/Master's/PhD in STEM (Mathematics, Computer Science, Engineering)
• Excellent knowledge of data science tools, including, python coding, SQL and production tools
• A deep understanding of probability and statistics fundamentals
• A big-picture mindset to correctly diagnose problems, produce research, and discover solutions
• Excellent communication and collaboration skills to partner with Product Owners and business heads

Job Description:

They’re looking for next-level Data Scientists to board our FinTech rocket ship and shape the future of financial services apps. Phew! It’s a big task, but you won’t do it alone. You’ll be working with the toughest and most gifted professionals in Product, Design, Data Science and Engineering, on impactful projects that’ll make their company move forward

Responsibilities:

• Building models for full Retail Credit lifecycle
• Improving existing algorithms and building new Proofs of Concept
• Delivering real impact to the product through rigorous data-driven solutions
• Researching and then delivering PoCs into data products
• Collaborating with product owners, engineers, and data scientists to continually solve complex data problems

 

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