ABOUT TRIPACTIONS

TripActions is the fastest-growing corporate travel platform disrupting a $1.5T industry and shaping the future of business travel.

TripActions is a story of inspiration born of frustration. Road warriors and co-founders Ariel Cohen and Ilan Twig believed that companies deserved a travel solution that takes the pain out of work trips –– so that their travelers can focus on being productive and meeting in-person, not wasting valuable time booking travel. So in 2015, they created TripActions. Since then, we’ve been a mission to power the face-to-face, in-person connections that move people, ideas and businesses forward.

TripActions’ platform offers a vast selection of inventory that travelers can choose from, a personalized, intuitive user interface driven by machine learning, and 24/7 proactive real human, customer support. Companies enjoy complete travel program visibility, over 30% cost savings on average and seamless integrations with their HR and expense systems.

Globally, TripActions has grown to over 600 employees across 7 offices in 4 countries. We support over 1,500 customers, with innovative brands like Lyft, Dropbox, Sara Lee Frozen Bakery, Allbirds, Robinhood and the ACLU relying on TripActions for their business travel needs. As one of Silicon Valley’s newest “unicorns”, TripActions has a valuation north of $1B and a total of $232M in funding. We’ve recently received $154M in our Series C funding round –– led by new investor Andreessen Horowitz, with participation from repeat investors Lightspeed Venture Partners, Zeev Ventures and SGVC.

TripActions was recently recognized as one of Fast Company’s Most Innovative Companies for 2019, #12 in LinkedIn’s Top Startups 2018 and #3 in the U.S. for Happiest Employees by Comparably.

We’re redefining what it means to travel for work. Come help us build the future of business travel.

 

ABOUT THE ROLE

 

Part of our global Data team based from the EMEA Headquarters located in Amsterdam, you will work closely with stakeholders throughout the organization to transform data into data products and actionable insights and tools. The ideal candidate will be extremely curious and will their data skills and business mindset to make a difference every day. We are looking for people who can operate at a company that grows as fast as ours, by being able to deal with multiple moving pieces while still holding up quality, long term thinking and delivering value to our customers.

 

RESPONSIBILITIES

  • In partnership with business stakeholders, build and develop data science products like recommenders, predictive models, and customer and product segmentation. Tasks include:
    • Identifying business problem and translating them into successful data science implementations
    • Estimate how much time a project will require for completion, what are the bottlenecks, and staying on track regarding deliverables and deadlines
    • In partnership with Data Engineering, designing and implementing data flows to support and enable data products
    • Build, evaluate, deploy and monitor model(s) for the product
    • Build visualizations and insight dashboards to support usage and understanding of your data products
    • Implement controls in your products to ensure ongoing reliability and accuracy
  • Conduct advanced univariate and multivariate analysis on large data sets to generate insights and recommendations in projects like NPS sentiment analysis, A/B testing, drivers analysis, and "best customer" attribute modeling
  • As necessary, support the general data team with business reporting and analytics requests (max 25% of the time)
  • Provide business expertise and guidance (consultative partnership) on how to apply DS products and insights within business operations and strategy
  • Staying up to date with the latest developments in the area of data science

 

QUALIFICATIONS

  • Ph.D. or Masters in mathematics, statistics, computer science, or information science
  • 3+ years of work experience in Data Science
  • Experienced and proficient in machine learning/deep learning tooling, for example Python (including scipy, numpy, pandas, sklearn, tensorflow) , R and Spark
  • Experienced and proficient in using SQL to build and manage data sources for analysis
  • Experienced and proficient in modeling techniques like regression, dimension reduction, supervised and unsupervised learning, collaborative filtering, and deep learning (RNNs, CNNs, LSTMs)
  • Experienced in representing your findings and models via BI tools like Tableau
  • Familiar with development best practices in building data science products via tools like git
  • Ability to translate business opportunities and needs into analytics projects and data science products
  • Demonstrated ability to communicate complex analytics and models in "human interpretable" insights

 

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