At Contentful we are building a Marketing Growth team for rapid product experiments. We are looking for Data Engineers to power the data and event pipelines that ensure the team can make data driven decisions on the experiments and drive actions across our insight and decisioning tools. You will help design and implement tracking and data pipelines and contribute to designing and building strong data models that enable rapid and reliable decision making. You will work closely with Data Analysts, Product Managers, Engineers and Marketers to ensure the needs and priorities are understood. This role will be focused on the data engineering required to drive our Growth Team experiments including integrating with CRM systems, powering analysis and segmentation, and delivering the information required for reporting and self-serve discovery.

As a Product Data Analyst (f/m) you will partner with our product teams to help measure and understand the value we deliver to our customers. Your insights will be key to enable data driven decision-making of Product Development at Contentful. It lets developers and content creators work in parallel, increasing team efficiency and happiness. Companies such as Co-op, Spotify, Bang&Olufson, N26, Swarovski use Contentful to build their mobile and web products, voice controlled apps and more. We're growing rapidly and are backed by over $150 million in funding from top-tier venture capital firms like Sapphire Ventures, Salesforce Ventures, General Catalyst and Benchmark.

In this episode, I have a great conversation about chatbots, artificial intelligence, machine learning and much more with my guest Jordi Torras, the founder of Inbenta, who focuses on AI and Natural Language Processing for chatbots and search engines. ******************************* Questions Asked ******************************* Tell us about your background. Why do you focus on AI (artificial intelligence)? Do you think that computers will ever become self aware? Tell us about Inbenta. What is a chatbot? Do chatbots continually learn? How do chatbots work on the backend? Tell us about intents and utterances. How is machine learning helping chatbots know more? Explain what symbolic AI is? What is language? How do we embed a chatbot in the world that you want it to learn more about? What's the difference between learning and acquiring a language? What's the difference between AI, Machine Learning and Natural Language Processing? Give us an example of symbolic AI. Tell us about AIML? What kind of skills do developers need to have to work with chatbots? How do buyer personas affect a chatbot? What is sentiment detection? How do you give chatbots the company's personality? What is conversation flow and how is it set up? Is there a tool or standard for implementing conversation flow? How can we make chatbots more human like? What are your thoughts on avatars for chatbots? What is the uncanny valley or zombie affect? ******************************* Reference Links ******************************* Inbenta (https://www.inbenta.com/en/)