At a Glance
- Tasks: Transform complex data into actionable insights using AI and machine learning.
- Company: Join Barclays, a leading financial institution with a commitment to innovation.
- Benefits: Competitive salary, health benefits, and opportunities for professional growth.
- Other info: Work in a dynamic environment with excellent career advancement opportunities.
- Why this job: Make a real impact by driving strategic growth through data analytics.
- Qualifications: Proficiency in statistical analysis, Python programming, and data manipulation.
The predicted salary is between 60000 - 80000 € per year.
Join us as a Senior Data Scientist at Barclays, where you'll be responsible for transforming complex data into actionable insights that drive strategic growth and innovation. You'll harness AI and advanced machine learning techniques to transform raw data into strategic insights that drive business decisions and competitive advantage.
Qualifications you should have:
- Statistical analysis and modelling – proficiency in applying statistical methods/modeling to data.
- Programming in Python – ability to code in Python and contribute to codebases.
- Data manipulation – experience querying large datasets (SQL / PySpark).
Some other highly valued skills may include:
- Machine learning / AI expertise – advanced knowledge of ML/AI algorithms and their applications.
- Financial domain knowledge – understanding of banking products, risk frameworks, and regulations.
- Data visualization – ability to create compelling visual representations of complex data insights.
This role can be based in London, Glasgow or Northampton.
Purpose of the role:
To use innovative data analytics and machine learning techniques to extract valuable insights from the bank's data reserves, leveraging these insights to inform strategic decision-making, improve operational efficiency, and drive innovation across the organisation.
Accountabilities:
- Identification, collection, extraction of data from various sources, including internal and external sources.
- Performing data cleaning, wrangling, and transformation to ensure its quality and suitability for analysis.
- Development and maintenance of efficient data pipelines for automated data acquisition and processing.
- Design and conduct of statistical and machine learning models to analyse patterns, trends, and relationships in the data.
- Development and implementation of predictive models to forecast future outcomes and identify potential risks and opportunities.
- Collaborate with business stakeholders to seek out opportunities to add value from data through Data Science.
Assistant Vice President Expectations:
- Advise and influence decision making, contribute to policy development and take responsibility for operational effectiveness.
- Collaborate closely with other functions and business divisions.
- Lead a team performing complex tasks, using well-developed professional knowledge and skills to deliver on work that impacts the whole business function.
- Set objectives and coach employees in pursuit of those objectives, appraisal of performance relative to objectives, and determination of reward outcomes.
- If the position has leadership responsibilities, People Leaders are expected to demonstrate a clear set of leadership behaviours to create an environment for colleagues to thrive and deliver consistently excellent standards.
- The four LEAD behaviours are: Listen and be authentic, Energise and inspire, Align across the enterprise, Develop others.
- For an individual contributor, lead collaborative assignments and guide team members through structured assignments, identifying the need for the inclusion of other areas of specialisation to complete assignments.
- Identify new directions for assignments and/or projects, identifying a combination of cross‑functional methodologies or practices to meet required outcomes.
- Consult on complex issues; providing advice to People Leaders to support the resolution of escalated issues.
- Identify ways to mitigate risk and develop new policies/procedures in support of the control and governance agenda.
- Take ownership for managing risk and strengthening controls related to the work done.
- Perform work that is closely related to that of other areas, which requires understanding of how areas coordinate and contribute to the achievement of the objectives of the organisation sub‑function.
- Collaborate with other areas of work, for business‑aligned support areas to keep up to speed with business activity and the business strategy.
- Engage in complex analysis of data from multiple sources of information, internal and external sources such as procedures and practices (in other areas, teams, companies, etc.) to solve problems creatively and effectively.
- Communicate complex information – such information could include sensitive information or information that is difficult to communicate because of its content or its audience.
- Influence or convince stakeholders to achieve outcomes.
All colleagues will be expected to demonstrate the Barclays Values of Respect, Integrity, Service, Excellence and Stewardship – our moral compass, helping us do what we believe is right. They will also be expected to demonstrate the Barclays Mindset – to Empower, Challenge and Drive – the operating manual for how we behave.
Senior Data Scientist in Glasgow employer: hackajob
At Barclays, we pride ourselves on being an exceptional employer, offering a dynamic work culture that fosters innovation and collaboration. As a Senior Data Scientist, you'll have access to cutting-edge technology and the opportunity to work alongside industry experts in vibrant locations like London, Glasgow, or Northampton. We are committed to your professional growth, providing ample opportunities for development and a supportive environment that encourages you to thrive while making a meaningful impact on our strategic goals.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Data Scientist in Glasgow
✨Tip Number 1
Network like a pro! Reach out to current or former employees at Barclays on LinkedIn. A friendly chat can give you insider info and maybe even a referral, which can really boost your chances.
✨Tip Number 2
Prepare for the interview by brushing up on your technical skills. Make sure you can confidently discuss your experience with Python, SQL, and machine learning techniques. Practice explaining complex data insights in simple terms – it’s all about making it relatable!
✨Tip Number 3
Showcase your problem-solving skills during interviews. Be ready to tackle hypothetical scenarios or case studies that demonstrate how you’d approach data challenges. This is your chance to shine and show how you can add value to the team!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining the Barclays team.
We think you need these skills to ace Senior Data Scientist in Glasgow
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Senior Data Scientist role. Highlight your experience with statistical analysis, Python programming, and data manipulation. We want to see how your skills align with what we're looking for!
Showcase Your Projects:Include specific projects where you've used machine learning or AI techniques. We love seeing real-world applications of your skills, so don’t hold back on sharing those success stories!
Be Clear and Concise:When writing your cover letter, keep it clear and to the point. Explain why you're a great fit for the role and how you can contribute to our team at Barclays. We appreciate straightforward communication!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at hackajob
✨Know Your Data Inside Out
Before the interview, dive deep into your past projects involving data analysis and machine learning. Be ready to discuss specific examples where you transformed complex data into actionable insights, as this will showcase your expertise and relevance to the role.
✨Brush Up on Python and SQL Skills
Since programming in Python and querying large datasets with SQL are key requirements, make sure you can demonstrate your coding skills. Consider preparing a small project or example that highlights your ability to manipulate data effectively.
✨Showcase Your Financial Knowledge
Understanding banking products and risk frameworks is crucial for this role. Familiarise yourself with relevant financial concepts and be prepared to discuss how your data science skills can add value in this context.
✨Prepare for Collaborative Scenarios
As collaboration is a big part of the job, think of examples where you've worked with stakeholders to drive data-driven decisions. Highlight your ability to communicate complex information clearly and influence outcomes, as this aligns with the expectations of the role.