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Lead Data Scientist

People are at the core of Fareportal. We are one of the fastest growing travel technology companies in the world; our portfolio of travel brands, including flagship product CheapOair, receives over 100 million visitors annually. 

We are looking for a Lead Data Scientist to join our team in New York City. As a data scientist at Fareportal, your primary focus will be on building large-scale, big data-driven revenue management predictive models. In this role you will partner closely with world-class talent across web, advanced analytics and business groups to improve our pricing models. You will have some of the richest and most robust data at your fingertips across multiple subject areas (e.g., travel trends, flight patterns, clickstreams, bookings, marketing campaigns) and an opportunity to work in an entrepreneurial environment to quickly see your efforts drive meaningful business impact.


  • Working on a cross-functional team of data engineers, web developers and business unit owners to improve existing pricing algorithms.
  • Supporting our data modeling efforts to ensure we’re capturing the data needed to improve our modeling capabilities.
  • Engaging directly with our web and A/B testing teams to implement and monitor performance of our data science products.
  • Collaborating with directors, managers, and our senior leadership team to ideate and introduce new data science innovations into business areas such as web, UI/UX, marketing and fraud.
  • Using a variety of techniques including predictive modeling, recommendation engines, revenue management, conversion rate optimization, and site and user experience optimization.
  • Other ad-hoc projects


  • 5+ years Python experience, 2 year Spark experience
  • BA, BS or related degree in CS, Information Systems or similar discipline.MS or above preferred
  • Experience in managing teams of 4-6 members
  • Must be well versed in languages such as Python, R, SQL, Spark, Power BI, Data Bricks, and have a strong understanding of machine learning, statistical and probability analysis, predictive modeling, hypothesis testing and associated software libraries and tools
  • Advanced skills and training in machine learning data mining and other quantitative research analytics such as non-linear regression analysis, multivariate analysis, Bayesian methods, generalized linear models, decision trees and random forest, non-parametric estimations, neural networks, ensemble models, etc..
  • Worked in cloud-based environments such as AWS or Azure, and are familiar with relevant technologies and languages (e.g. Hadoop, MapReduce)
  • Understand query databases easily and run various models to extract new features and identify important variables.
  • Connected different types of datasets in different forms and can handle potentially incomplete data sources.
  • Worked with implementing models in high-traffic ecommerce and web environments

What we offer

  • Plenty of vacation time
  • Flexible work hours
  • Medical, dental and vision benefits
  • Flexible spending accounts
  • Travel benefits
  • Team outings
  • Corporate discounts
  • Breakfast bar
  • Unlimited coffee
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