Data Scientist
We are currently looking for a Data Scientist to join our Data Labs team based in London.
The Experian DataLabs UK&I and EMEA are based at WeWork Kings Place (London Kings Cross area).
We are a 14 people team, consisting of PhD-level data scientists, data analysts, engineers, and managers.
We spur innovation for Experian by creating brand new (ML-driven) products or by replacing existing solutions using advanced ML.
The team is dedicated to advanced R&D, and benefits from the mentality and drive of a start-up, combined with the backing of a resourceful corporation. This environment encourages innovation by supporting ambitious, rewarding and risky projects, even if they're likely to fail.
The datasets we play with include all of Experian's data (e.g., credit bureaux, fraud databases, company databases, market databases, transactional databases) and also datasets provided by external partners.
We provide solutions in not only the credit risk space, but also in fraud, marketing, pricing, customer management, sports analytics, etc.
During development of our products we work closely with internal Experian units and/or external partners, originating from a wide range of business sectors, such as banking, fintech, retail, insurance, and even sports.
We love Python and its wider PyData ecosystem and perform our analyses on our own 11-node Hadoop cluster (e.g., via PySpark or Scala) and/or a couple of fast GPU-driven machines.
Position summary
The role requires that you have an extensive background in machine learning and data mining. A proven track record in inventing and modifying advanced innovative algorithms, and applying them to large data sets to solve difficult business problems, is essential.
You can find some videos about the DataLabs here, here, and here.
Key job functions
We are looking for:
It would be fantastic if you also have
The Experian DataLabs UK&I and EMEA are based at WeWork Kings Place (London Kings Cross area).
We are a 14 people team, consisting of PhD-level data scientists, data analysts, engineers, and managers.
We spur innovation for Experian by creating brand new (ML-driven) products or by replacing existing solutions using advanced ML.
The team is dedicated to advanced R&D, and benefits from the mentality and drive of a start-up, combined with the backing of a resourceful corporation. This environment encourages innovation by supporting ambitious, rewarding and risky projects, even if they're likely to fail.
The datasets we play with include all of Experian's data (e.g., credit bureaux, fraud databases, company databases, market databases, transactional databases) and also datasets provided by external partners.
We provide solutions in not only the credit risk space, but also in fraud, marketing, pricing, customer management, sports analytics, etc.
During development of our products we work closely with internal Experian units and/or external partners, originating from a wide range of business sectors, such as banking, fintech, retail, insurance, and even sports.
We love Python and its wider PyData ecosystem and perform our analyses on our own 11-node Hadoop cluster (e.g., via PySpark or Scala) and/or a couple of fast GPU-driven machines.
Position summary
The role requires that you have an extensive background in machine learning and data mining. A proven track record in inventing and modifying advanced innovative algorithms, and applying them to large data sets to solve difficult business problems, is essential.
You can find some videos about the DataLabs here, here, and here.
Key job functions
- Applying, modifying, and inventing algorithms to solve challenging business and technical problems.
- Evaluating the predictive ability of client and Experian data sets (and combinations of). Advising on optimal data-gathering strategies.
- Documenting and presenting, internally and externally, model process and model performance.
- Engaging and influencing business leaders in solution path design.
- Mentoring junior members of the team, if appropriate.
- Championing a culture where the fair treatment of customers is at the heart of Experian's business.
We are looking for:
- An advanced degree (PhD preferred) in Computer Science, Physics, Engineering, Mathematics or a similarly quantitative field.
- At least 2 years' of postgraduate or industry experience in topics such as machine learning, data mining, analytics, and predictive modelling.
- A scientific mentality with the ability to ask the right questions, as well as answer them.
- A proven track record in developing, innovating, and applying advanced algorithms to address practical problems and in building new analytical products.
- Demonstrated ability to lead and execute projects from start to finish.
- Deep knowledge and experience with several learning techniques such as clustering, regression, neural networks, SVMs, trees, and ensemble methods such as random forests and boosting.
- Proficiency in Python and preferably in some of Scala, Java, C/C++, R.
- Experience with Linux
It would be fantastic if you also have
- Worked with GPUs and have used CUDA programming.
- Experience with graphical models, Bayesian networks, Gaussian processes, MCMC, hidden Markov models and social network analysis.
- Experience with deep learning techniques for text, voice processing and modelling.
- Applied agile methods for software development