At a Glance
- Tasks: Join our team as a Data Analyst, focusing on data analysis and reporting.
- Company: Handelsbanken is a relationship bank with a strong local presence and a commitment to customer service.
- Benefits: Enjoy competitive salary, private medical insurance, and a generous pension contribution of 15%.
- Why this job: Be part of a diverse analytics team and contribute to impactful data-driven decisions.
- Qualifications: Strong communication skills, SAS knowledge, and a passion for data analysis are essential.
- Other info: We value diversity and encourage everyone to apply, regardless of background.
The predicted salary is between 48000 - 84000 £ per year.
The Risk Models and Data team within the Risk function is responsible for stress testing model and tool development and maintenance, risk data analytics, the regular production of a number of MI reports on various risk topics and risk data governance.
The role is for a Data Analyst to work within the Data Analytics workstream of the team. This is a great opportunity for an analytics professional to be part of a diverse analytics team and be actively involved in a broad range of initiatives such as supporting and improving regular management information reporting, ongoing improvement projects and data governance.
The role will suit a strong communicator, with strong SAS skills, that can collaborate cross-functionally and apply their technical skills to support the data analysis and data driven decision making capabilities of the Risk function.
Main Responsibilities- Run regular production of MI and ad-hoc requests for data analysis
- Support the development of robust data analysis for both ad-hoc and regular management reporting
- Support the development of efficient management information (MI) production
- Support the resolution of Data Quality issues and the Data Lineage activities of the team
- Support the build out of a robust data governance and data quality process within the risk function
- A strong communicator who can collaborate cross-functionally
- Have relevant experience working with data analysis within financial services
- Have an intermediate knowledge of SAS and SQL; and be eager to develop further
- Have a good understanding of risk/financial terminology and be interested in developing this knowledge further
- Be comfortable working with various MS Excel features such as formulas and pivot tables. Knowledge of Power BI is also desirable; but not mandatory
Handelsbanken is a relationship bank with a decentralised way of working, a strong local presence thanks to a nationwide network of branches, and a long-term approach to customer relations. Each Handelsbanken branch operates as a local business enabling it to make decisions at a local level and provide a bespoke service. The focus is always on the need of the individual customer and not on the sale of specific products.
The Bank is deeply committed to embedding good equality and diversity practice into all of our activities. This is so that we are an inclusive, welcoming and inspiring place to work that encourages everyone to apply, regardless of socio-economic background, age, disability, pregnancy and/or parental status, race (including colour, nationality, and ethnic or national origin), veteran status, marital and civil partnership status, religion or belief, sex, gender reassignment or sexual orientation.
At Handelsbanken, we deeply value our unique culture and values including trust in and respect for each individual. We take pride in nurturing a work environment where people flourish, and where they are empowered to take decisions in their areas of expertise. We take a long term perspective in everything we do and want each employee who joins us to build a long terms successful career with the Bank.
What is in it for you?- We have a wide range of learning and development available, empowering and enabling our colleagues to take ownership of their own development.
- Competitive Salary and an extensive range of benefits is provided, including private medical insurance, income protection and life assurance
- A market-leading pension contribution of 15% paid by the bank, which can be invested in a wide range of funds (including ESG and Shariah funds)
Your journey with us begins once you have submitted your application. One of our Handelsbanken recruiters will be reviewing your details and will later organise a phone conversation if you match the role requirements. If there is a mutual fit, we will extend an invitation for you to participate in an interview.
How can we support you to be your best self? Our Talent Acquisition team will be happy to provide support e.g. if you need additional time to prepare for an interview or you have any requirements for any part of the interview/hiring process – just let us know by email uk_talent@careers.handelsbanken.co.uk.
This advert will be live for a minimum of two weeks. However, please note that after the two weeks, the closing date could change at any time depending on the number of responses received.
Data Analyst with SAS employer: Handelsbanken
Contact Detail:
Handelsbanken Recruiting Team
uk_talent@careers.handelsbanken.co.uk
StudySmarter Expert Advice 🤫
We think this is how you could land Data Analyst with SAS
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, especially SAS and SQL. Consider taking online courses or tutorials to enhance your skills and demonstrate your commitment to learning.
✨Tip Number 2
Network with current or former employees of Handelsbanken on platforms like LinkedIn. Engaging with them can provide you with insider knowledge about the company culture and the role, which can be invaluable during interviews.
✨Tip Number 3
Prepare to discuss your experience with data governance and quality processes. Think of specific examples where you've successfully resolved data quality issues or improved reporting processes, as these are key responsibilities for the role.
✨Tip Number 4
Showcase your communication skills by preparing to explain complex data analysis concepts in simple terms. This will highlight your ability to collaborate cross-functionally, which is a crucial aspect of the role.
We think you need these skills to ace Data Analyst with SAS
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with data analysis, particularly in financial services. Emphasise your SAS and SQL skills, as well as any relevant projects that demonstrate your ability to support data-driven decision making.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific aspects of the job description that resonate with you, such as your interest in risk data analytics and your commitment to data governance.
Showcase Communication Skills: Since the role requires strong communication skills, provide examples in your application of how you've successfully collaborated with cross-functional teams. This could be through past projects or experiences where effective communication was key.
Highlight Continuous Learning: Mention any ongoing education or training related to data analysis, SAS, or risk management. This shows your eagerness to develop further and aligns with the company's commitment to learning and development.
How to prepare for a job interview at Handelsbanken
✨Showcase Your SAS Skills
Since the role requires strong SAS skills, be prepared to discuss your experience with SAS in detail. Bring examples of projects where you've used SAS for data analysis, and if possible, demonstrate your problem-solving approach using SAS during the interview.
✨Understand Risk Terminology
Familiarise yourself with key risk and financial terms that are relevant to the role. This will not only help you answer questions more effectively but also show your genuine interest in the field and your commitment to developing your knowledge further.
✨Prepare for Data Quality Discussions
The job involves resolving data quality issues, so be ready to discuss your experience with data governance and quality processes. Think of specific examples where you've identified and resolved data quality problems in previous roles.
✨Demonstrate Strong Communication Skills
As a strong communicator, you’ll need to collaborate cross-functionally. Prepare to share examples of how you've successfully communicated complex data insights to non-technical stakeholders, highlighting your ability to make data-driven decisions accessible to everyone.