Data Scientist

As a Barclays Data Scientist, get an exciting opportunity to develop and deploy machine learning applications that achieve transformative outcomes in support of and for BUK and our customers. Your primary focus for this role is on writing rigorous and robust code to underpin better pricing, marketing, and affordability models, as well as advanced customer and channel analytics. These models in turn power new commercial propositions, enhanced efficiencies, and excellent risk controls.

Barclays is one of the world's largest and most respected financial institutions, with 329 years of success, quality, and innovation behind us. We offer careers that provide endless opportunity – helping millions of individuals and businesses thrive and creating financial and digital solutions that the world now takes for granted.

Working Flexibly

We’re committed to providing a supportive and inclusive culture and environment for you to work in. This environment recognizes and supports ways to balance your personal needs, alongside the professional needs of our business. Providing the opportunity for all our employees, globally to work flexibly empowers each of us to work in a way that suits our lives as well as enabling us to better service our customers’ and clients’ needs. Whether you have family commitments or you’re a carer, or whether you need study time or wish to pursue personal interests, our approach to working flexibly is designed to help you balance your life. If you would like some flexibility, then please discuss this with the hiring manager, and your request will be reviewed subject to business needs.

This opportunity is location flexible. We will consider requests for locating the role at an alternative Barclays’ key UK office from that advertised.

We are currently in the early stages of implementing a hybrid working environment, which means that many colleagues spend part of their working hours at home and part in the office, depending on the nature of the role they are in. We’re flexible on how this works and it may continue to change and evolve. Depending on your team, typically this means that colleagues spend a minimum of between 20% to 60% of their time in the office, which could be over a week, a month, or a quarter. However, some colleagues may choose to spend more time in the office over a typical period than their role type requires. We also have a flexible working process where, subject to business needs, all colleagues globally can request work patterns to reflect their personal circumstances. Please discuss the detail of the working pattern options for the role with the hiring manager.

What will you be doing? 

• Designing and delivering transformative data science projects as part of diverse, multifunctional teams, utilising a diverse range of data sources
• Identifying and applying appropriate analytical techniques in building predictive and prescriptive models  
• Building Python applications to extract, transform, and examine various types of data, especially at scale and for constructing robust pipelines often combining multiple sources
• Developing and deploying machine learning applications using DevOps tools and in accordance with governed patterns of production
• Translating modelling approach and outputs into business implications that are interpretable and exciting to non-technical audiences through persuasive and transparent presentations
• Spearheading exploration of data in various forms and from multiple sources, and handling data mismatch and inconsistencies to extract relevant insights useful for the business
• Documenting own code appropriately so it is easily readable, repeatable, and extensible, and conducting peer review on the code of other colleagues in the team

What we’re looking for: 

• Experience building standard supervised (GLM, ensemble techniques) and unsupervised (clustering) models in prior professional roles, and an understanding of standard industry libraries (pandas, sklearn, keras etc)
• Proficiency in big data technologies (spark, dask) and databases (SQL, NoSQL)
• Significant understanding of and expertise in Python, including writing unit tests, building packages, and writing reusable/maintainable code
• Ability to understand and explain modelling techniques and visualise analytical results (e.g., matplotlib/seaborn/plotly/D3/tableau)

Skills that will help you in the role:

• Skilled at pitching ideas and analytical results to connect with people in a way that has impact and influence
• Understanding and demonstrated evidence of building analytical solutions in an industry setting
• Prior usage of continuous integration/development tools (e.g., Jenkins and Spark ML pipelines)
• Experience in any of these specialist areas: reinforcement learning, NLP, Bayesian techniques/generative models

Where will you be working?

We will confirm your place of work at the point of offer, ensuring that this is considered in line with our future ways of working and overall location strategy.


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