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Data Scientist

We are looking for a Data Scientist to help us blaze some trails and join our growing efforts in data science, machine learning and predictive modelling. You’ll combine techniques in NLP, image analysis, deep learning and more to touch nearly every aspect of the business and be a champion for data driven culture.  

A little bit about you:

  • MS or PhD in a quantitative field (e.g. physics, mathematics, statistics, computer science, economics...), PhD or relevant long term research experience preferred.
  • You have experience with and thrive working on large projects independently and as a member of a small, accomplished team.
  • You are not afraid to push back to find the best solution.
  • You relish working in a fast-moving, challenging and collaborative environment.
  • You love the challenge of breaking down large, difficult problems, acquiring new knowledge and iterating.

What impact will you have on Unbounce?

  • Working with our R&D team, you will be able to apply machine learning to automatically improve customer web page conversion rates.
  • You’ll have the opportunity to build customer-facing products that utilize machine learning.  
  • The data and predictive models you use and create will drive important business decisions.
  • You'll be supporting our internal testing program to ensure we make key decisions from a data driven perspective. We currently use an advanced Bayesian testing methodology.
  • You’ll act as a mentor for all things statistics and data science.

What you can learn in this role:

  • You’ll be exposed to machine learning techniques on unstructured web page data, topic modelling, other NLP techniques and convNets to name a few.
  • Dig deep with advanced experiment design utilizing state-of the art sequential Bayesian techniques.
  • Tackle user behaviour modelling.
  • Participate in large-scale project planning and stakeholder education.
  • Building your knowledge around different techniques - we’re always open to exploring other options!

Your experience includes:

  • Working knowledge of SQL, familiarity with one or more NoSQL implementations a plus.
  • Extensive knowledge of either R or Python and their associated data science/machine learning packages.
  • You have knowledge of basic experiment design and are comfortable running split tests.
  • You have a foundation of knowledge in machine learning: understanding of supervised and unsupervised learning, knowledge of several algorithms in each, loss functions, regularization, bagging and boosting.
  • You have a solid understanding of fundamental statistics and mathematics: inference, Bayesian methods, likelihood estimation, decision theory, Monte-Carlo methods and sampling theory; multivariable calculus; partial differential equations; numerical integration.

Bonus experience in:

  • Convolutional and recurrent neural networks, deep learning and image analysis a plus.
  • Spark
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