A strong contributor role accountable for increasing the FC Data Analytics and Machine Learning capability within Santander UK by combining a wide range of technical skills with business knowledge to turn vast quantities of data into value.
The role will build data products (data sets, analysis, models etc.) and tools to drive hypothesis generation, FC models calibration and decision making; creating actionable metrics and designing effective experiments.
The difference you'll make.
Identifying, assessing, managing and reporting risks, taking proactive personal responsibility for 'doing the right thing' in compliance with regulatory requirements
Calibrating FC models/analysis to mine large volume of data, extract insights
Exploring opportunities for improvements and communicating outputs to engineering and product management to drive product decisions with data
Managing and delivering specific initiatives and projects on on-going topic agendas within the portfolio under its remit
Contributing to the implementation of the FC Data Analytics roadmap through the analysis and supply of information to support strategic activities across the business
Managing a team of more junior Data Analysts and coaching them to help to achieve desire outcomes
Must have experience of at least 1 of the following: Python, SQL or SAS
Knowledge of Data Analytics techniques with evidence of using this across some or most of the following business problems: numeric prediction, classification & product recommendation business problems
It would also be nice for you to have.
Degree level or equivalent in a numerical subject such as Financial Crime analytics, physics, engineering or applied maths.
Knowledge of Financial Crime data needs, processes and systems
Experience with Big Data, Python, Hive, impala and SAS
Proven experience of being able to present to both technical and non technical audiences
If there's anything we can do in the recruitment process to help you achieve your best, get in touch. Whether it's a copy of our application form in another format or additional assistance, we're available through telephone, email, or face to face. You can contact us at email@example.com or call 0870 414 9080.