Data Scientist - Upside Travel

Washington, DC

Job Category: Data Science Industry: E-commerce Annual Salary: commensurate with experience

Data Scientist - Decision Sciences & Pricing

To apply, please visit: https://jobs.lever.co/upside/487eb81e-f3f6-43c4-918f-5506483ccf06

We are an ambitious, well-funded startup with plans to change a $1 trillion-dollar global industry. This is no ordinary startup. We have a proven management team that has done it before, done it before together, and done it before in the travel industry. The company is overflowing with fiercely intelligent people who have tons of energy and an upbeat view of the future. We all act like owners and we get a huge kick out doing great work and doing it fast. We like it even more when we come up with a fresh way to solve a problem. Above all, we are devoted to solving customer problems, because that’s at the center of everything of we do.

ABOUT YOU
- You’re an experienced data scientist with skills honed on internet commerce scale information and comfortable contributing to and improving a production system.
- Comfortable operating within an agile environment working with cross disciplined teams
- Excited about working in a python production and DS stack and have defendable positions on which tools you choose.
- You’ve got proven experience with pySpark and MLlib and have delivered scalable decision systems as part of a team
- Believe ML can be a powerful tool when combined with human in the loop domain expertsIntrigued by the challenge of what a machine based travel agent could look like
- We’d like to see demonstrated knowledge in one or more of the following areas
- Delivering recommendation systems with direct experience tuning models for personalization at consumer internet scale
- Implementation and continuous improvement of a pricing system. Background in pricing theory and building market driven pricing system highly desiredExperience with modeling and implementing a loyalty program

ABOUT THE GIG
- We put the customer first - our goal is to reduce their cognitive load, provide transparent and actionable recommendations and improve the business trip with data and machines. All work you’ll do is in direct support of that data science mission.
- You’ll listen directly to customers, identify opportunities and form hypothesis. Build prototypes and test them in production. Iteration and measurement are essential parts of what we do.
- Be integral part of a cross-discipline team including product, engineering and UX that’s looking to redefine the travel shopping experience from a data-centric point of view.
- Refine and improve a decision system that powers our unit economics. Understand and simulate impact of changes to company wide KPIs.
- Help build a data powered narrative that we can repeatedly deliver to our customer at scale and with high fidelity.
- Refine and improve our systems that mine large scale travel marketplace data, our consumer purchase behavior and the traveler experience timeline.

ABOUT US
We are positive, passionate, playful, and always pushing to be better. Our team is a hodgepodge of challenge seekers, travel gurus, startup junkies, and data-miners who see the big picture.

 

YOU WANT TO TALK TO US IF…
· You are motivated by disrupting the norm.
· You have a great sense of humor and take your profession seriously, but not yourself.
· Your entrepreneurial spirit drives your bias for action.
· You are all about constructive feedback - you can dish it out and you can take it.
· You thrive in the frenetic energy of a startup.

WHAT WE OFFER
·  Competitive salary + equity
·  Full health, vision, and dental coverage
·  401K plan
·  Open paid time off
·  Impromptu Nerf gun battles

 

To apply, please visit: https://jobs.lever.co/upside/487eb81e-f3f6-43c4-918f-5506483ccf06 

Upside Travel is an equal opportunity employer and encourages people of all backgrounds, genders, ethnicities, abilities, and sexual orientations to apply. We are committed to being an inclusive place to work, while maintaining a workforce that represents the communities we serve.

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