We are looking for a FrontEnd Software Engineer, for our Machine Learning Experience Team with a real passion for solving complex and exciting problems. Over the last year, the team has been directly responsible for launching exciting Machine Learning features in Momentive helping customers gain insights into their data. The team is responsible for building ML Models, backend services and frontend implementation. The team is encouraged to take big swings, support each other, deliver features and value and make a difference for the customer. Momentive (NASDAQ: MNTV), maker of SurveyMonkey, is a leader in agile experience management, delivering powerful, purpose-built solutions that bring together the best parts of humanity and technology to redefine AI.

We are looking for a summer intern to join our product data science team to develop algorithms for important product initiatives for Momentive. We are equipped with rich product data ranging from text to image and video. We build ML models to solve customer issues. We work with Machine Learning engineers to ship models in production seamlessly. Therefore you will see the business impact of the models quickly.

Social listening and analysing online reviews is extremely insightful when it comes to understanding your audience and their relationship with your brand. But what if you have a specific line of questioning in mind? Perhaps you want customer feedback immediately after a product launch, and there isn't enough data online yet. Or maybe you'd like to explore what your customers are saying in more depth. Surveys are a popular way to garner specific information from your audience, but unless you know how to analyse survey data effectively, the process can be time-consuming and may not give you the insights you need.

Momentive (NASDAQ: MNTV) (formerly SurveyMonkey) is a leader in agile experience management, delivering powerful, purpose-built solutions that bring together the best parts of humanity and technology to redefine AI. Momentive products, including GetFeedback, SurveyMonkey, and its brand and market insights solutions, empower decision-makers at 345,000 organizations worldwide to shape exceptional experiences. More than 20 million active users rely on Momentive to fuel market insights, brand insights, employee experience, customer experience, and product experience. Ultimately, the company's vision is to raise the bar for human experiences by amplifying individual voices. We are looking for a Sr Data Scientist who will design data science projects including experimentation, Survival Analysis, Topic modeling, and classifications.

The CTO of Momentive, formerly SurveyMonkey, discusses the importance of machine learning and AI as the world of data continues to grow. SurveyMonkey has been one of the big names associated with online surveys since its inception more than 20 years ago. The company first came to Dublin in 2014 and subsequently added a European data centre to its Irish footprint in 2019. But while the well-known name remains attached to the surveys product, the company behind the product rebranded as Momentive earlier this year. Robin Ducot joined in 2017 as chief technology officer and leads engineering and infrastructure at the company from her base in San Francisco.

Momentive (formerly SurveyMonkey) is a leader in agile experience management, delivering powerful, purpose-built solutions that bring together the best parts of humanity and technology to redefine AI. Momentive products, including GetFeedback, SurveyMonkey, and its brand and market insights solutions, empower decision-makers at 345,000 organizations worldwide to shape exceptional experiences. More than 20 million active users rely on Momentive to fuel market insights, brand insights, employee experience, customer experience, and product experience. Ultimately, the company's vision is to raise the bar for human experiences by amplifying individual voices. The Machine Learning Platform (MLP) team's charter is to build out a machine learning platform that accelerates the efficient adoption of machine learning across all Momentive portfolio products.

Momentive (formerly SurveyMonkey) is a leader in agile experience management, delivering powerful, purpose-built solutions that bring together the best parts of humanity and technology to redefine AI. Momentive products, including GetFeedback, SurveyMonkey, and its brand and market insights solutions, empower decision-makers at 345,000 organizations worldwide to shape exceptional experiences. More than 20 million active users rely on Momentive to fuel market insights, brand insights, employee experience, customer experience, and product experience. Ultimately, the company's vision is to raise the bar for human experiences by amplifying individual voices. Our Data Infrastructure team makes up a portion of our Global Data team for Momentive.

SurveyMonkey (Nasdaq: SVMK), is a leader in agile software solutions for customer experience, market research, and survey feedback. Our mission is to power the curious and enable organizations, including 98% of the Fortune 500, to transform feedback into action. Our brand is beloved and well known throughout the world--over 6 billion people have taken a SurveyMonkey survey! Today, more than 17 million active users rely on our platform to measure and understand feedback from employees, customers, website and app users, and the market. And our enterprise-grade products and solutions enable 335,000 organizations globally to solve daily challenges--from delivering better customer experiences to increasing employee retention.

This year, AAAI is launching a new invited speaker program highlighting AI researchers who have just begun careers as new faculty members or the equivalent in industry. Applications will be adjudicated by a committee consisting of the AAAI-21 chairs and a diverse group of AAAI Fellows. New Faculty Highlight talks will be allotted 30 minutes each; the aim is for these talks to broadly survey the candidate's research to date. Several talks will be released online and publicized each day of the AAAI conference, following which they will be available archivally as part of the conference program. Invited speakers will be further invited to contribute an article to a corresponding series in AI Magazine.

Just like with the answer prediction feature, Jonathan and his team also didn't have any previous data to go on for the "Build it for me" feature. This meant they had to set up the conditions for another scale effect. There was never a precedence for the Build It For Me feature: you either chose to create a survey from scratch or you chose from one of the templates available. With the Build It For Me feature, you simply pick a target audience and a survey goal (which in Janice's case was getting feedback). Then you'd go on to choose the right template because that would then narrow down the options from 300 to 4. Because they had no previous data to work with, the data scientists weren't involved for this feature.