Do you want to solve practical problems using machine learning or deep learning? Are you tired of just working on research projects or statistical analysis and not actual machine learning? If your answer is a resounding ‘yes’ to one or both questions, then this role is for you. You will be part of a highly innovative team working on interesting and challenging problems, leveraging cutting edge technology to build personalised products and services used by millions of end-users. This role offers a competitive salary as well as paid trips to conferences, personal development programs and cross team fun activities.
As a Data Scientist You Will
Develop new machine learning and deep learning models that can be tested and deployed as fully functional models.
Implement and scale-up high-availability models and algorithms for personalisation products that serve hundreds of brands and millions of end-users.
Investigate and create experimental prototypes that work on specific domains and verticals.
Analyse large, complex data sets to reveal underlying patterns, correlations and trends quantitatively.
Support and enhance existing models to ensure better performance.
Set up and conduct large-scale experiments to test hypotheses and drive product development.
MSc degree or equivalent qualification in Artificial Intelligence, Machine Learning, Computer Science, Statistics, Mathematics, Physics or similar quantitative discipline
Proficiency in Python and SQL, and experience in developing and deploying models to a production system or for commercial use.
Hands-on skills in machine learning techniques with demonstration in academic publications and/or online competitions like KDD-Cup, Kaggle etc.
Familiar with one or more machine learning algorithms: content / collaborative filtering, NLP, non-linear/deep regressions, boosted trees, ensembles etc.
Thorough understanding of full modelling process: exploratory data analysis, feature engineering/selection, multi-layer cross validations
A good understanding of statistics (e.g., hypothesis testing, non-parametric methods)
Ability to work collaboratively and proactively in a fast-paced environment interacting with both a non-technical and technical audiences
A PhD in a quantitative subject
Experience in developing prediction models in e-commerce or digital marketing
Reasonable development knowledge in Java (or Scala)
Experiences with big data frameworks i.e. Spark, Hadoop, Kafka etc.
Previous experience with recommender systems
Commercial mindset and interest in digital and web content
A hacker’s mentality to problem solving
Comfortable in using open source technologies
Interest in keeping up with state-of-the-art machine learning by attending and submitting papers to relevant conferences
Knowledge or experience in developing/deploying to AWS or Azure
Knowledge of big data systems and NoSQL databases
Software to drive your web