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Data Scientist at Prix

London · Full Time
Inaccurate forecasting and sub-optimal pricing cost companies 10-20% of their revenues. Today there is no obvious choice of partner for mid-size companies to solve these problems. Prix wants to change that. Read More
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Job Description

We are a global team of visionaries, techies, scientists and designers working together to solve hard scientific problems with high commercial impact. We build stuff that works and solve tough engineering challenges. We innovate at speed and growth-hack our way to customer happiness.

It is important to us that the team feels valued and respected. This means flexible hours, remote working, transparent and fair compensation (salary and options), health-plan, and hardware budget. And, most importantly, that we have fun doing something we care about.

- Becoming an expert on the data-structures in our target-industries
- Using our in-house algorithms & Python to solve data problems
- Write production-level Python code for integration intro product
- Working very closely with our science & product teams
- Cleaning, structuring and analysing customer datasets

- 2 years of experience as a Data Scientist or Engineer
- Professional experience with Python and its scientific stack
- Writes production Python and comfortable with CI, agile etc
- Experience working in a startup or similar environment
- Somebody who loves what they do and is genuinely passionate

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What We're Building

Only 10% of the world’s 190,000 hotels use revenue management software. Revenue management decision support adds 5-10% to the revenues of this £400 billion industry. The total addressable market for software decision support for mid-size hotel revenue managers is £500 million.

Prix uses technology developed in finance and engineering to understand hotel bookings at a deeper level and understand combinatorial complexity. This makes it possible to reduce reliance on historical patterns and make better decisions. We differentiate by being a tech-led company in hospitality (most competitors are the inverse).

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