Are you interested in building high-performance, globally scalable Financial systems that support Amazon's current and future growth? Are you seeking an environment where you can drive innovation? Does the prospect of working with top engineering talent get you charged up? If so, Amazon's Finance Technology (FinTech) is for you! As a Software Development Engineer in FinTech Treasury, you will build real time financial calculation engines and reports to assess Amazon's exposure to financial risks, and use Machine Learning (ML) to forecast cash balances across the company.

TD's own Brett Henry will be presenting at ITB Asia in Singapore on 17 October. Henry will interview guests Ken Kuguru, managing director, Asia Pacific at Egencia (based out of Singapore), and Samantha Williams, regional director, account management Asia Pacific at Travelport. They will talk about how the inevitable advent of artificial intelligence (AI) and machine learning (ML), combined with the already-mainstream use of big data,will affect our industry, with a focus on corporate / business travel. Egencia together with its global alliance partners cover 15 countries in Asia Pacific with Egencia dedicated points of sale in China, India, Australia, Hong Kong, Singapore and New Zealand. Kuguru is focused on driving growth throughout the region and optimizing technology and innovation to enhance the customer experience.

The last decade has seen a tremendous proliferation of Big Data. And Big Data Analytics, that is inadvertently tied to powerful Machine Learning technology. Fundamentally, Big data is just large amounts of data -- large in terms of volume, variety, veracity as well as velocity. This makes Big Data especially complex for traditional analytical methods to master, decrypt and/or simplify. Machine Learning, on the other hand, is an advanced application of AI that automates analytical model building.

I'm sure everyone who has been following tech industry news knows about "big data" and "AI." Although there is no industry-consistent definition for either term, most people tend to agree that both have been playing more and more important roles lately, and that we need to know and leverage them better in both our personal and professional lives. But wouldn't it be interesting if we looked beyond the marketing hype for a moment and talked about the people who are solving real business problems by using these technologies, who they are, which skills they have, and what they actually do? If you think so, continue to read on and we'll share with you some practical aspects of what's behind the scenes of data science and analytics at LinkedIn. With the mission to "Drive understanding and impactful decision making through rigorous use of data," the Analytics team at LinkedIn has been growing at a fast speed, with no sign of slowing down (currently have 20 team openings worldwide).