Golang (nice to have)
weka (nice to have)
Python (advanced) We are looking for Senior Data Scientists to work remotely on a data science projects that form a RTB exchange. We process over 10M requests/s and all teams constantly face with high volume, low latency and geo-distributed challenges.
We value technical excellence and you will have both resources and time to deliver world-class code.
This is a 100% remote position
, for qualified candidates we help with visa and relocation to Wrocław, Poland.
You will be working with team members in NYC and Poland.
We are happy to negotiate higher compensation if you are an ideal candidate.
In this role you will be working on the conception, design, development, testing, and deployment of real-world applications of models & data that impact billions of dollars of marketing spend.
From optimizing real-time bidding auctions, to separating human from non-human web traffic, to building out a global cross-device graph across billions of users, you will have the opportunity to work on numerous cutting-edge problems and develop scalable, high-performance solutions to big data problems using state-of-the art technologies, languages and frameworks.
If you think you are a good fit even though you don’t meet all requirements – please apply, we are currently filling multiple roles and will do our best to find the best match.
- BS, Masters, or PhD degree with 5+ years of industry experience in a quantitative discipline
- Experience in implementing projects in Tensorflow (preferred) or scikit-learn or Pytorch.
- Solid understanding of machine learning techniques and algorithms, such as k-NN, Naive Bayes, SVM, Decision Forests
- Experience with data visualization tools, such as for example D3.js
- Practical programming experience (for example Python/Scala or Golang)
- Previously participated in deploying Machine Learning Models all the way from research to production pipeline
- Design and develop Machine Learning models and algorithms
- Partner closely with Engineering on the architecture and implementation of modeling efforts to ensure performance and scalability
- Work seamlessly with Product and Analytics to define concrete measures of success, including business level goals as well as improvement of outcomes
- Develop tools and processes to monitor performance of existing models and implement enhancements to improve scalability, reliability, and performance