Senior Data Scientist

Globally, 1.7 billion people lack a bank account while two thirds out of this population have a mobile phone. The Experian MicroAnalytics started from this observation to become a gateway between the Telco and the banking world. We bring high risk management standards to the mobile world through our solutions with the permanent objective to fast-track deployments. The MicroAnalytics products and services individually assess the risk and opportunity of offering specific products and services to telco subscribers and mobile wallet users, thereby helping telcos increase ARPU, reduce churn, grow purchase volume and ultimately increase consumer satisfaction.

The MicroAnalytics business today provides products and services to clients in Europe, Asia, the Middle East, Africa and South America. By combining multiple Telco data attributes, we build a Telco score that empowers Financial Institutes to make more informed decisions on credit applications for bureau invisible or thin file clients.

We are currently looking for a Senior Data Scientist to join our team and support the Experian MicroAnalytics by leading an advanced research and development; enhance relationship with client and develop and provide new innovative solutions. The role holder will be responsible for guiding the team in inventing and modifying advanced innovative algorithms and applying them to large data sets to solve complex business problems. The role holder must be able to balance and prioritise multiple projects; anticipate obstacles, and deliver high quality outputs.

What you'll be doing:

Be responsible for the design and delivery of new business solutions to clients; Understand and anticipate client needs; Design a business solution and ensure the team can deliver successfully

Ensure full understanding of client requirements and be responsible for developing new solutions and enriching their product base.

Oversee and facilitate the training of a range of Machine Learning models; evaluate the quality of the trained models, using existing and new measures

Lead the process of building a model (churn, propensity or loss) using Decision Analytics data to be used for business strategy that will impact outcomes

Design data structure and data storage schemas to efficient data manipulation and information retrieval

Develop data driven models to quantify the value of a given data set; Validate score performance

Continuously work on identifying opportunities for automation supporting his/her ideas with cost/benefit analyses justifying the need both internally within the team and towards external stakeholders

Develop appropriate business cases to increase MicroAnalytics global reach and client base

Maintenance and improvement of the existing model development pipeline

What you are expected to bring:

A degree (BSc level) at a numerical discipline, such as Computer Science, Mathematics, Statistics and econometrics, Physics, etc.

5-7 years of experience in DS (design AI/ deep learning solutions)

Previous experience/participation in client facing projects

Strong grasp of probability, statistical inference, optimization algorithms, linear algebra, and calculus.

Understanding of how and when to apply key analytical approaches including regression analysis and machine learning

Strong grasp of techniques for model cross-validation and penalizing unnecessary complexity, including regularization, in-sample vs out-of-sample.

Ability to write near-production-level code in at least one general purpose programming language (e.g. Python, C++).

Flexible and adaptable to learn and understand new technologies

Demonstrable analytical and problem-solving abilities, coupled with an enquiring mind and the ability to learn quickly

A keen eye for detail, good at spotting problems and quickly proposing solutions.

Strong verbal and written communication skills (fluency in English)

Any of the following abilities and skills will be considered an advantage:

Good knowledge of OOP principles, data structures, algorithms & design patterns

Experience with deep learning and other advanced modeling approaches to extract and automate insights from data.

Experience with Reinforcement learning algorithms for decision/strategy optimizations.

Exposure to Linux.