Company: Context Scout
Role: Apply Machine Learning/data science to work on applying statistical modelling to web browsing behaviour data
Context Scout is building a web browser that helps you browse the web. Right now, web browsers render webpages but do not understand the content or how it relates to previous webpages or searches. This forces us to keep tabs open, do hundreds of searches, take notes and so on, meaning it takes work to do work online. With Context Scout, the web browser is transformed into a dynamic interface to information that adapts to your ongoing task, searches for information on your behalf and connects you to your favourite apps.
Context Scout’s MVP is being used by beta testers in over 100 companies worldwide and is backed by top investors in the UK and US. The research behind the tech originated in UCL and has been developed for over 6 years before the company was founded at Entrepreneur First 2 years ago.
You’d be joining a team that has extensive entrepreneurial, academic and commercial experience who loves operating at the intersection of deep machine learning research and obsessive user experience.
Context Scout (in collaboration with UCL) are looking for 2 machine learning/data science engineers to work on applying statistical modelling to web browsing behaviour data and contribute to academic research.
You should have:
• Solid previous experience in solving large analytical problems using statistical, machine learning or other quantitative methods (e.g. supervised/unsupervised learning, graphical models, time series analysis, statistical testing)
• B.S. degree (or higher) in Computer Science or Electrical Engineering (or equivalent experience)
• Solid programming skills in at least one of, Python, Scala, C/C++ or Java (Python is preferred).
• Self-motivated researcher with ability to work on industrially relevant research
Experience with some of the following is a plus:
• Working with machine learning, information retrieval, web search, NLP, knowledge bases and graph frameworks such as Pandas, scikit-learn, NumPy or SciPy
• Working in a research team
• Working in a fast-paced startup environment
How to apply:
Please complete this online application form + send your CV to email@example.com