Are you ready to be a big part of something big? For 25 years we've been evolving with the new economy to help people choose how they move today and tomorrow. When it comes to your career, we want to provide big opportunities to help you make a big impact. But for this to be possible, we strive to feel small. Small enough to quickly change tack, small enough to learn from different departments and small enough to connect authentically with leadership.

Launched in 1998, this pioneering British-born brand has specialised in creating amazing experiences and unforgettable memories - from hotels, city breaks and holidays to theatre, entertainment and spa days. Experts in brightening up online travel, lastminute.com is among the worldwide leaders in the field, helping hundreds of thousands of customers every year find, and do, "whatever makes them pink". Lastminute.com is part of Lm group, publicly traded multinational Group, among the worldwide leaders in the online travel industry. Every month, the Group reaches across all its websites and mobile apps (in 17 languages and 40 countries) 60 million unique users that search for and book their travel and leisure experiences. More than 1,200 people enjoy working with us and contribute to provide our audience with a comprehensive and inspiring offering of travel related products and services.

At Tekion, we're building the only cloud-native platform that is transforming the automotive retail industry, leapfrogging it into the future and providing unparalleled customer experience. We're creating seamlessly integrated, elegant, and intuitive solutions built with cutting edge technology and powered by Big Data, Machine Learning (ML)/ AI and Internet of Things (Connected vehicle to connected devices). We're harnessing passion, entrepreneurial spirit, deep industry expertise and the latest technologies to create something very special. We're inventing new technology along the way to overcome barriers and solve big problems, all while having a blast doing it! The Data Sourcing Specialist requirements include sourcing and obtaining various memberships, relationships, 3rd party applications, access points and information needed throughout Tekion.

YipitData is the leading market research firm for the disruptive economy and recently raised $475M from The Carlyle Group at a valuation of over $1B. We analyze billions of alternative data points every day to provide accurate, detailed insights on ridesharing, e-commerce marketplaces, payments, and more. Our data team uses proprietary technology to identify, license, clean, and analyze the data many of the world's largest investment funds and corporations depend on. For three years and counting, we have been recognized as one of Inc's Best Workplaces. We are a fast-growing technology company backed by Norwest Venture Partners and The Carlyle Group.

Find open roles in Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), Computer Vision (CV), Data Engineering, Data Analytics, Big Data, and Data Science in general, filtered by job title or popular skill, toolset and products used.

As technology and data capabilities advance, there is an increasing focus on leveraging data that will enable innovation and deliver new value for customers. Geospatial data is an emerging area of opportunity in the property sector, and it is fast being utilised by agile "proptechs", developers and data scientists. Buildings, like everything, occupy space. For residential and commercial enterprises, the contextual data attached to properties is fertile ground for innovation. Whether helping property developers better understand the spatial contexts of sites or providing homebuyers with easier access to the detail they need, geospatial data is being used more than ever to create solutions that deliver value across the sector.

Data lakes contain much more information than CFOs and other executives typically use to track performance, say data specialists. Companies are missing opportunities to grow revenue and improve margins by approaching the data they collect too narrowly, data specialists said in a SaaStr webcast last week. Many software-as-a-service (SaaS) companies are investing heavily in data collection, but they're only analyzing the most obvious results in their metrics, like churn. They can get a more accurate picture of performance, more quickly, by using AI to analyze a broader range of data, even if it's not obvious how it relates to a metric, said Berit Hoffmann, vice president of product at data analysis software company Sisu. One large business-to-business SaaS company Sisu worked with started seeing unusually heavy churn even though one of the main data points they look at regularly showed no change.

Joining a geology team, the Geoscience Data Specialist will play a vital role in the continual development of our digital transformation tools and our geoscience analytic techniques. You will be working alongside our geoscience experts to analyse geological data workflows and develop the database and dynamic data-driven improvements. You will be responsible for maintaining consistency and integrity of the corporate database and for the development of shared resources for workflows. The successful candidate will be responsible for supporting the development and implementation of technologies and efficient workflows to extract, transform, load, manipulate, explore, analyse, report, and visualise data for operational and legacy projects. You will work on projects to assist with data identification, inventory, extraction, transformation and database loading and will also develop, manage and apply ETL tools, scripts and database systems for geoscience data.

The shortage of qualified data scientists is often highlighted as one of the major handbrakes on the adoption of big data and AI. But a growing number of tools are putting these capabilities in the hands of non-experts, for better and for worse. There's been an explosion in the breadth and quality of self-service analytics platforms in recent years, which let non-technical employees tap the huge amounts of data businesses are sitting on. They typically let users carry out simple, day-to-day analytic tasks--like creating reports or building data visualizations--rather than having to rely on the company's data specialists. Gartner recently predicted that workers using self-service analytics will output more analysis than professional data scientists. Given the perennial shortage of data specialists and the huge salaries they command these days, that's probably music to the ears of most C-suite executives.

You might have noticed a comment was made on the first article in this series: I didn't mention the'why' as a KSF in bringing home a machine learning project. And it's true, forgetting the why is a serious problem. As the commenter noted: Unless there's a why and a businessperson involved, all you've got is a handicapped specialty group who have been given tools, but not told what to do with them. So here's my amended list of KSFs for a machine learning project: The why is the business reason for the project. It's rarely as exciting or motivating as the technology involved. But it pays the bills.