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We’re Aggero - an exciting new startup in esports tackling the advertising and sponsorship space. Our goal is to make it easier for gamers to make money that doesn’t sell out their audience, by linking only the most appropriate brands to the most appropriate audiences. This also means we’re going to be able to help brands figure out how to spend their money in the esports space efficiently - meaning brands get their message out to the appropriate people - saving time and money whilst maximising ROI!

The Co-founders are all young, gamers and have amassed a significant experience in tech, P.E, finance, blockchain, machine learning and social media, having founded companies with successful exits and have built significant credibility throughout their work in these spaces. As gamers, they are genuinely passionate about what they do. At Aggero, we work hard, but we definitely play hard.

We’re currently looking for a fun, talented and experienced full stack data developer/scientist to join our team on a short term basis with potential to join on a longer term basis with negotiable salary. 

The role will involve building a use case demonstration of a powerful data-driven esports marketing platform.

The tech stack includes at scale data scraping from several sources including reddit, twitch gaming, youtube gaming and social media, with the ability to then deploy efficient data structuring algorithms, for use in a wide array of machine learning applications. Data sources will include chat data, emoji data, reddit and social media comments, video frame data and audio stream data. This data stack will then be utilised for NLP, computer vision and statistical matching applications, with the end goal of being able to identify key in market segments and intrinsic value of various esports athletes, brands and teams.

Our ideal person would be someone who is great working in a team of multicultured people, from all over the world with a variety of different backgrounds (The co-founders are Romanian, British and Italian, working with a team based in the USA and London, with Investors from India, Singapore, the USA and many other places), and analytical thinkers with a flair for creative solutions to tough problems. They would have experience working in startups from both a software development and a data science background, with particular experience in building and deploying large scale production grade big data applications. They should be able to fully understand our back-end framework in order to aid in designing a lightening efficient front-end for its deployment.

We would expect you to have an awareness of (and an ability to transition between) most of the following languages, programming frameworks and areas with not too much difficulty, with major experience in a few that enable you to fully deploy an efficient data stack (from data acquisition and structuring to storage and model deployment):

  • Ruby 
  • Node JS 
  • Python, R (Particularly data management analysis packages such as pandas and tensorflow)
  • PHP 
  • Hadoop, Hive, Spark 
  • Java 
  • Javascript 
  • Pig 
  • Scala 
  • C/C++
  • SQL 
  • noSQL 
  • Spark 
  • Kafka 
  • React 
  • Angular 
  • Docker 
  • DynamoDB 
  • Azure/Watson/AWS/Google Cloud 
  • JSON 
  • MongoDB 
  • Go 
  • ML (NLP, Computer Vision)

Statistics Education: most people we work with have earned a BS or equivalent in Statistics, Computer Science, Math, Physics, or an applied quantitative field and likely added an MS or PhD in the same field. Having said that, we’re open to conversation and we understand that you can’t often portray true value with a degree. If you can prove your worth to us, we will listen with open minds and if you’ve got what it take, we really don’t care what you studied at college or if you went at all. We just care about the best person for the job.

If you are a team orientated, fun, motivated, talented person, with an eye for creative problem solving, chances are you’ll fit our company like a glove. Get in touch with us if you think this role seems right, we’d love to hear from you!

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