Dataseat was founded just over a year ago by two industry veterans and Entrepreneurs David Philippson & Dr Paul Hayton with the goal to change and improve the way App marketers run their programmatic media campaigns.
The company provides a Bidder or DSP as a service to App marketers to in-house programmatic media buying for user acquisition and re-engagement. Dataseat also provides analytics to support clients with insight on fraud, attribution accuracy and incrementality to help marketers build the business case to in-house and take control of the media strategy.
Dataseat is backed by industry leading VCs and Angel Investors. The role will sit within the Data Science team and you will be part of the programmatic advertising in-house revolution, developing contextual ML models, producing insight for our customers and supporting product and commercial teams.
We operate in a big data environment, receiving in excess of 250,000 qps (queries per second) which we have to score in real time and respond within milliseconds with a decision to bid or not.
The role is very hands-on, and If you are keen to join an early stage startup within the ad-tech industry and be part of a fantastic team then this is the opportunity for you. This role will provide huge opportunities for growth as it is such a pivotal role which will have an immediate impact on the business.
- You will join our team of Java Engineers based in London.
- Building libraries and services for Dataseat’s core bidding platform.
- Support of the Machine Learning team through feature engineering.
- Degree Computer Science, Maths, Physics or other numerate subject, or relevant experience. Experience in online mobile advertising is a plus.
- 3+ years experience with Java.
- Exposure to Scala or Spark would be an advantage.
- Exposure to, or willing to learn Big Data Technologies.
- Experience of performance microservices at scale is a big plus.
- Good communicator who can explain and understand complex problems while dealing with both non-technical and technical teams.
- A focus on details and willingness to learn.
- Share Options
- London based but opportunity to work from home several days a week (currently all the employees are working remotely full time).