Overview

Data Scientist

We are Qubit:

Qubit is the leader in highly persuasive personalization at scale. Leading eCommerce companies work with Qubit to transform the way they understand and influence their customers in order to increase revenue, build loyalty and improve marketing efficiency.

By combining rich customer data, deep learning technology and advanced segmentation capabilities, the Qubit Customer Influence Engine can precisely match customers with the widest range of personal, online experiences to influence behavior at scale.

Qubit is trusted to deliver real impact to the bottom line for the biggest brands in eCommerce including Ubisoft, CafePress, Topshop, Shiseido, and Emirates. Across the global Qubit customer base, $600 million worth of online sales are influenced over a typical week.

The Data Science team…

…helps us to develop intelligent products around data and conduct cutting-edge research into consumer behaviour on the web. The team conducts real R&D around human behaviour. Our data collection tools store more than 1 billion data points every day. Overall, Qubit technology tracks consumer journeys leading to billions of pounds of online spending worldwide every year, for some of the largest names in online retail.

We’re looking for someone smart and motivated, with experience solving large and complex data problems with statistical and machine learning techniques. As part of our research team you’ll help to understand our ever-growing dataset, working closely with other parts of the business to ensure our products are best in market.

Responsibilities:

  • Joining a team of Data Scientists at a fast-growing company with plenty of opportunities to have a big impact.
  • Conducting pure research and developing that research into real products used by some of the top names in online retail.
  • Building statistical models and applying machine learning/artificial intelligence techniques to understand consumer behaviour online.
  • Working with a mixed set of technologies and experimenting with new ones.
  • Exploring how state-of-the-art machine learning methods can be applied to real-life problems at Google-scale

Requirements:

We’re open to applicants from any background. Our main requirement is that you’re smart, motivated, and able to do the job. We don’t mind what specific technologies you’ve worked with in the past, although, having some previous experience with production-quality Python will help you add value quicker. We’re looking for someone who adds to our team and complements the skills we already have. That said, in order to meet these requirements, you will probably have:

At least one of:

  • A PhD with a large data-analysis and statistics component (e.g. Machine Learning, Computer Vision, High Energy Physics, Genetics etc…)
  • A MSc in Applied Statistics, Machine Learning or similar
  • Commercial data science experience
  • Experience deploying machine learning models in a production environment

At least two of:

  • Experience conducting data analysis on big data (e.g. TB+ scale datasets).
  • Experience applying statistical techniques and machine learning algorithms to extract insights from real data.
  • Strong technical skills.
  • Ability to clearly communicate complex research findings with non-technical team members and clients
  • An interest in human behaviour

At Qubit, we champion diversity and are proud to be an equal opportunity employer. We embrace difference with open arms and see it as a huge benefit to our community. We are dedicated to equal opportunity regardless of race, colour, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or veteran status. If you have a disability or need that requires accommodation, please let us know.

Qubit is an equal opportunity employer committed to providing its employees with a work environment that is both challenging and rewarding. For additional information, please visit our website at www.qubit.com

Tagged as: data science, deep learning, machine learning, Python