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Lead Data Scientist
2 months ago
TBO–( is a global platform that aims to simplify all buying and selling travel needs of travel partners across the world. The proprietary technology platform aims to simplify the demands of the complex world of global travel by seamlessly connecting the highly distributed travel buyers and travel suppliers at scale.
The TBO journey began in 2006 with a simple goal – to address the evolving needs of travel buyers and suppliers, and what started off as a single product air ticketing company, has today become the leading B2A (Business to Agents) travel portal across the Americas, UK & Europe, Africa, Middle East, India, and Asia Pacific.
Today, TBO’s product range from air, hotels, rail, holiday packages, car rentals, transfers, sightseeing, cruise, and cargo. Apart from these products, our proprietary platform relies heavily on AI/ML to offer unique listings and products, meeting specific requirements put forth by customers, thus increasing conversions.
TBO’s approach has always been technology-first and we continue to invest on new innovations and new offerings to make travel easy and simple. TBO’s travel APIs are serving large travel ecosystems across the world while the modular architecture of the platform enables new travel products while expanding across new geographies.
Why TBO:
• You will influence & contribute to “Building World Largest Technology Led Travel Distribution Network” for a $ 9 Trillion global travel business market.
• We are the emerging leaders in technology led end-to-end travel management, in the B2B space.
• Physical Presence in 47 countries with business in 110 countries.
• We are reputed for our-long lasting trusted relationships. We stand by our eco system of suppliers and buyers to service the end customer.
• An open & informal start-up environment which cares.
Key Expectations:
• More than 5 to 9 years of experience working as a data scientist/ML Engineer with exposure to the following technologies – Python, PySpark, SQL, Airflow and Docker
• Experience and understanding of with LLMs, deep learning
• Knowledge of GIT for SCM.
• Expertise in statistical modeling, machine learning, and data mining techniques.
• Proficiency in programming languages (Python, R, SQL).
• Experience with big data technologies (Hadoop, Spark).
• Extensive experience with cloud platforms (AWS, GCP, Azure).
• Excellent organizational and time management skills.
• Self-driven, flexible, and innovative.
