Our Vision
FLYR is focused on the relentless application of advanced and intuitive technologies that help transportation leaders unlock their ultimate potential.
FLYR is a technology company that is purpose-built for the travel industry. Leveraging deep learning, an advanced form of AI, FLYR is helping airlines, cargo, and hospitality businesses around the globe elevate their results. With FLYR, businesses are able to improve revenue performance and modernize the e-commerce experience through accurate forecasting, automation, and analytics.Flight Itinerary (About The Role)
FLYR is on a mission to build the modern AI-enabled operating system for airlines. An important part of this mission is to develop a context-aware and data-driven revenue optimization system.
In this role, you will work on neural network based pricing and forecasting models to improve the performance of FLYR’s revenue management product. Airline revenue management is a complex field with many legacy applications and is in much need of disruption. Successful outcomes will make a significant contribution to the state-of-the-art and empower airlines around the world to better compete.
We are a customer-centric and product-focused data science organization. We value ownership, technical excellence, bias towards action and delivering results to our customers. We are looking for highly passionate and capable team mates who are force multipliers.
This position is located in the U.S. and the ideal candidate will be able to join us in our San Francisco office.
Come onboard and lead FLYR to new heights with us!
What Your Journey Will Look Like (Responsibilities)
- Work with product and data science management to develop key results for given product objectives.
- Work with other technical product owners, lead data scientists and data science managers to develop technical solutions.
- Act as a technical lead on projects aiming to improve performance of core pricing models and deliver results.
- Own and actively contribute to the design and development of internal pricing, forecasting and optimization libraries.
- Define and maintain science and engineering best practices in the form of processes.
- Lead code reviews to identify issues, root causes and solutions.
What To Pack For This Trip (Qualifications)
- Demonstrated ownership, bias for action and detail orientation through past experience.
- Demonstrated ability to communicate technical work to technical and non-technical audiences.
- Demonstrated ability to distill complex technical requirements down to modular, robust and maintainable systems designs.
- In-depth understanding of machine learning and artificial neural networks.
- 5+ Years experience as a Machine Learning Scientist, Data Scientist, or equivalent building decision or prediction systems at industrial scale.
- 2+ Years experience in applying artificial neural networks to prediction/regression problems at industrial scale.
- Demonstrated ability to iteratively improve artificial neural network models through methodical experimentation.
- Strong software engineering skills and demonstrated ability to build enterprise-grade ML applications.
- Demonstrated ability to step into a sophisticated technology stack and develop an understanding of its inner workings.
- Demonstrated ability to develop a solid understanding of the business domain and its relation to model/system performance.
- Strong data analysis skills and willingness to dive deep into data to identify root causes and drivers.
- Demonstrated ability to provide guidance to junior engineers and scientists in technical areas.
Optional Carry-On (Preferred Qualifications)
- Exposure to time-series analysis and forecasting.
- Exposure to pricing algorithms and revenue management.
- Experience working with Google Cloud Platform and Vertex AI.
First-Class Amenities
- Equity in Series C startup with high growth potential
- Comprehensive healthcare plans (Choice of PPO & HMO available)
- Generous PTO policy and flexible working arrangements
- 401K with company match
- Free breakfast/Lunch (in-office)
- 100% paid Parental Leave for 12 weeks
- Annual educational fund