Are you passionate about applied machine learning research? Are you open-minded about approaches and techniques, willing to pick the best tool for the job? Would you like to work with an exciting live dataset spanning billions of rows?
Would you like to see how your insights and models influence the purchasing habits of millions of people?
Are you keen on working with world class teammates in a successful startup to bring a product to the market that will change a billion-Dollar industry? Well, this position might be just for you!
SO1 is the leading artificial intelligence for retail.
We are building a revolutionary AI promotion platform based on machine learning and seamless retail integration. The SO1 Engine learns autonomously about individual consumer’s preferences and their willingness-to-pay, providing real-time targeting across various media channels in the form of individual promotion feeds. Working with leading retailers in Europe and North America, SO1 has proven its superior ability to serve up the right offers to consumers while at the same time maximizing financial impact for retailers and globally recognized brands.
SO1 has been backed by high-profile investors with 8-figure investments and continues to focus on building the best AI for retail.
We offer our employees unique learning opportunities and the chance to take on important projects from day one.
You will track the state of the art in various areas of Machine Learning and Deep Learning, Operations Research and Optimization
You will come up with ideas for models, prototype them, deploy to production and run A/B tests
You will develop mathematical abstractions covering business needs in flexible ways
You will communicate ideas, capabilities and workflows to business stakeholders
You will be working both independently and in small focus teams on the full project lifecycle – from project inception to monitoring production results
You are an open-minded polymath craving for transforming your ideas into real-world impact.
A curious, creative, analytical mindset open for ideas coming from: econometrics, statistics, physics, machine learning, neuroscience and psychology
Love for rapid, hands-on prototyping with tight feedback loops
Strong familiarity with fundamentals in statistics, probability theory, information theory and linear algebra
Strong core computer science, data structures and algorithms
Experience in building custom ML algorithms and pipelines from scratch
Deep familiarity with Python, Unix and SQL
Experience working with very large datasets and live production systems
Experience with gradient boosting and/or deep learning
Experience with either of: representation learning, semi-supervised learning, reinforcement learning, natural language processing, ranking & recommendation, metaheuristics and optimization, generative models
Bonus points for
Public activity in the ML scene (Kaggle, papers, conferences, meetups, videos, open source projects)
Background in fintech/adtech/research