At a Glance
- Tasks: Analyse data and provide insights to drive business decisions in a leading British bank.
- Company: Join one of the largest financial institutions with a rich 300-year history.
- Benefits: Flexible work options, health insurance, and support for professional development.
- Other info: Dynamic team environment with excellent career growth opportunities and a focus on diversity.
- Why this job: Make a real impact by transforming data into powerful stories that influence key decisions.
- Qualifications: Strong analytical skills, experience with Snowflake, AWS, SQL, and Python.
The predicted salary is between 37800 - 46200 £ per year.
Our client is a British bank, one of the largest financial companies in the world. The bank was founded three centuries ago, and today its assets are estimated at trillions of US dollars.
Throughout its history, the bank has offered various banking products to clients. Its technical support has become more complex and expensive due to the expansion of its product line and the growth of its customer base. The development of technology has led to growing customer expectations for banking apps, as well as the automation of bank account interactions. Therefore, it became clear that all the IT systems of our client needed an upgrade. Now they have been improved in accordance with modern technologies, and the user interfaces of the apps have been modernized as well. The main goal of the project is to migrate data and reports from on-premises infrastructure to Snowflake/AWS.
The role focuses on using advanced analytics, translation and visualisation skills to consult with business stakeholders, gain a deep understanding of their business needs, and proactively and reactively offer data and analytics expertise and solutions to business challenges in line with the bank’s strategic goals.
Responsibilities:
- Deeply understand the needs of business stakeholders using strong consultancy skills to identify suitable data and analytics solutions to meet those needs in order to support the achievement of business strategy, ensuring data is sourced from approved Golden Sources, is used appropriately and is fit for purpose.
- Drive and embed advanced analytics in their team to develop business solutions which increase understanding of the Client’s business, including its customers, processes, channels and products.
- Bring advanced analytics to life through visualisation to tell powerful stories and influence important decisions for key stakeholders, using the best tools and approaches, blending both the data and insights and the stakeholders’ needs.
- Work in an agile way within multidisciplinary data and analytics teams, leading, coaching and coordinating resources, either direct reports and/or more widely from across the team and the business, to plan and deliver strategic agreed project and scrum outcomes.
Requirements:
- Leadership skills and a passion for data and analytics.
- Experience coaching and supporting colleagues to succeed.
- Hands-on experience with Snowflake and AWS.
- Experience with AWS Glue and Apache Airflow.
- Strong SQL and Python skills.
- Proven experience migrating code from on-premises environments to the cloud.
- Experience building data pipelines and extracting data from different data sources.
- Reporting development experience with at least two of the following: Tableau, Power BI, and Amazon QuickSight.
- Advanced analytics knowledge.
- Ability to simplify data into clear visualisations and compelling insights.
- Experience using appropriate systems and tools for data analytics and visualisation.
- Knowledge of data architecture, key tools and relevant coding languages.
- Strong knowledge of data management practices and principles.
- Experience translating data and insights for key stakeholders.
- Good knowledge of data engineering, data science and decisioning disciplines.
- Strong communication skills with the ability to engage with a wide range of stakeholders.
We offer:
- Vacation as per the laws of your country.
- Health insurance for you and your loved ones.
- Pleasant environment with corporate parties and get-togethers.
- Comfort service for solving technical and everyday problems at work.
Data Analyst employer: DataArt
DataArt is an exceptional employer that fosters a collaborative and innovative work culture, particularly for those passionate about AI in the Healthcare & Life Sciences sector. With a strong emphasis on employee growth, you will have access to cutting-edge projects and the opportunity to lead transformative solutions that make a real difference in people's lives. Located in a vibrant tech hub, DataArt offers unique advantages such as flexible working arrangements and a commitment to professional development, making it an ideal place for talented individuals seeking meaningful and rewarding careers.
StudySmarter Expert Advice🤫
We think this is how you could land Data Analyst
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like DataArt!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Analyst at DataArt.
✨Leverage Professional Networks
Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like DataArt.
✨Apply Directly through Our Website
When you find a suitable opening like Data Analyst at DataArt, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Analyst
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at DataArt, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at DataArt. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at DataArt
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at DataArt!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
