Data Scientist

Data Scientist

PAYE only

Length: 3 months (the contract may be extended to 6 months)

Working hours: 9-5 PM

About the role:

In this role, you will use a combination of computing, mathematics and statistics to understand employee behaviour as well as to improve our work environment and employee experience in order to help colleagues achieve their ambition, in the right way. The perfect candidate will have a background in a quantitative or technical field, will have experience working with large data sets, and will have some experience in data- driven decision making. They are likely to have strong experience in machine learning and will have worked within relevant academia and/or industry. The role will be using cutting edge data science techniques to extract information from people data.

What will you be doing?

• Deliver ideation, design, analysis, prototyping and deployment of Data Science products, powered by scalable machine learning models in coordination with other members of the team
• Be a subject-matter-expert in traditional statistical methods (Logistic/Linear Regression, GLM, Decision Trees) as well as new Machine Learning algorithms (k-Means, Random Forest, Gradient Boosting etc.)
• Follow best practice and the internal procedures to collaborate with others in a compliance way
• Work closely with other Data Scientists and members from other guilds within the People Analytics team (i.e., Project Managers, Data Visualisation, Organizational Behavioural Scientist, Data Acquisition etc.) to efficiently deliver projects from business proposal to a final product or reports

What we’re looking for:

• Financial services background is advantageous
• Bachelor/Master degree or equivalent competency in Mathematics, Statistics, Engineering, Computer Science or a related quantitative discipline
• Competencies in data analytics, including transforming raw data into meaningful and actionable intelligence. Able to provide meaningful answer to questions such us “so what?”, “what is next?”, “why?”
• Strong written and verbal communication skills including ability to explain sophisticated concepts to non-technical audiences
• Strong coding skills in Python, Able to work in Hadoop/PySpark and Hive. (code reusable and documented, usage of Git, able to create tests). Some exposure to R
• Be a subject-matter-expert in traditional statistical methods (Logistic/Linear Regression, GLM, Decision Trees) as well as new Machine Learning algorithms (k-Means, Random Forest, Gradient Boosting etc.)
• Be able to coordinate with others team members in an Agile way for a timely delivery. Usage of established artifacts and ways of work: peer-reviews, planning sessions, stand ups, retrospectives etc

Skills that will help you in the role:

• People Analytics related models and Survey (Questionnaire) analysis. Such as Exploratory Factor
• Analysis or Confirmatory Factor Analysis
• Familiarity with Visualization libraries such as Bokeh or Plotly
• Natural Language Processing, able to run topic modelling analysis
• Familiarity with People Analytics datasets. Such as headcounts and Workplace Analytics

About Barclays

Barclays is a British universal bank. They are diversified by business, by different types of customers and clients, and by geography. Their businesses include consumer banking and payments operations around the world, as well as a top-tier, full service, global corporate and investment bank, all of which are supported by their service company which provides technology, operations and functional services across the Group.

We are an equal opportunity employer and we are opposed to discrimination on any grounds.

Dynamic working gives everyone at Barclays the opportunity to integrate professional and personal lives, if you have a need for flexibility then please discuss this with the hiring manager.

Values 

Everything Barclays does is shaped by the five values of Respect, Integrity, Service, Excellence and Stewardship. Their values inform the foundations of their relationships with customers, clients, employees and contractors.