Data Analyst II

Data Analyst II

Street Full-Time 36000 - 60000 £ / year (est.) Home office (partial)
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At a Glance

  • Tasks: Analyse complex data sets to uncover insights and trends.
  • Company: Join a forward-thinking company that values data-driven decisions.
  • Benefits: Enjoy flexible work options, competitive pay, and professional development opportunities.
  • Why this job: Be part of a dynamic team that impacts business strategies through data.
  • Qualifications: Bachelor's or Master's in a relevant field with 2+ years of experience required.
  • Other info: Mentorship opportunities available for junior analysts.

The predicted salary is between 36000 - 60000 £ per year.

Responsibilities:

  • Collect, clean, preprocess, and analyze complex data sets from various sources to derive meaningful insights and identify trends.
  • Independently conduct data analysis and modeling to support business initiatives and solve complex problems.
  • Develop and maintain data reports, dashboards, and visualizations to effectively communicate findings to stakeholders.
  • Collaborate with cross-functional teams to understand their data needs and provide advanced analytical support.
  • Design and implement data quality checks and validation processes to ensure data accuracy and integrity.
  • Utilize statistical techniques and basic algorithms to uncover patterns and make data-driven recommendations.
  • Perform ad-hoc analysis and develop automated processes and tools to streamline data analysis workflows.
  • Stay updated on industry trends, best practices, and emerging technologies in data analysis and data management.
  • Mentor and provide guidance to junior data analysts, sharing your knowledge and expertise.

Job Qualifications:

  • Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.
  • 2+ years of experience in a data analysis role, demonstrating a strong understanding of data analysis techniques and methodologies.
  • Proficiency in data manipulation and analysis using tools such as SQL, Python, R, or similar.
  • Experience with data visualization tools such as Tableau, Power BI, or similar, to create interactive visualizations and reports.
  • Strong analytical thinking and problem-solving skills, with the ability to independently analyze complex data sets and draw meaningful insights.
  • Knowledge of statistical concepts and experience applying statistical techniques.
  • Excellent verbal and written communication skills to effectively present data findings and insights to stakeholders.
  • Ability to work collaboratively in a team environment and manage multiple projects simultaneously.
  • Strong attention to detail and ability to work with large datasets efficiently.

Data Analyst II employer: Breadfast

As a Data Analyst II at our company, you will thrive in a dynamic and collaborative work culture that values innovation and continuous learning. We offer competitive benefits, including professional development opportunities and mentorship from experienced analysts, ensuring your growth in the field of data science. Located in a vibrant area, our workplace fosters creativity and teamwork, making it an excellent environment for those seeking meaningful and rewarding employment.
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Contact Detail:

Breadfast Recruiting Team

StudySmarter Expert Advice 🤫

We think this is how you could land Data Analyst II

✨Tip Number 1

Familiarise yourself with the specific data tools mentioned in the job description, like SQL, Python, and Tableau. Having hands-on experience or projects showcasing your skills with these tools can set you apart from other candidates.

✨Tip Number 2

Network with current or former employees at StudySmarter through platforms like LinkedIn. Engaging in conversations about their experiences can provide valuable insights into the company culture and expectations for the Data Analyst II role.

✨Tip Number 3

Prepare to discuss specific examples of how you've used data analysis to solve complex problems in previous roles. Being able to articulate your thought process and the impact of your work will demonstrate your analytical thinking skills effectively.

✨Tip Number 4

Stay updated on the latest trends in data analysis and visualisation techniques. Mentioning recent developments or tools during your interview can show your commitment to continuous learning and your enthusiasm for the field.

We think you need these skills to ace Data Analyst II

Data Manipulation
SQL
Python
R
Data Visualization
Tableau
Power BI
Statistical Analysis
Analytical Thinking
Problem-Solving Skills
Data Cleaning
Data Preprocessing
Dashboard Development
Communication Skills
Collaboration
Attention to Detail
Project Management
Mentoring
Ad-hoc Analysis
Automation of Data Processes

Some tips for your application 🫡

Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the Data Analyst II role. Emphasise your proficiency in SQL, Python, R, and any data visualisation tools you've used, such as Tableau or Power BI.

Craft a Compelling Cover Letter: In your cover letter, explain why you're passionate about data analysis and how your background makes you a great fit for the position. Mention specific projects where you've successfully derived insights from complex datasets.

Showcase Your Analytical Skills: Provide examples of how you've used statistical techniques to solve problems or improve processes in previous roles. This could include any ad-hoc analyses or automated processes you've developed.

Highlight Collaboration Experience: Since the role involves working with cross-functional teams, mention any experiences where you've collaborated with others to meet data needs or support business initiatives. This shows your ability to work well in a team environment.

How to prepare for a job interview at Breadfast

✨Showcase Your Technical Skills

Be prepared to discuss your proficiency in SQL, Python, R, or any other relevant tools. Bring examples of past projects where you successfully manipulated and analysed data, as this will demonstrate your hands-on experience.

✨Prepare for Scenario-Based Questions

Expect questions that ask how you would handle specific data challenges or projects. Think about how you would approach cleaning data, conducting analysis, or creating visualisations, and be ready to explain your thought process.

✨Communicate Clearly

Since you'll need to present findings to stakeholders, practice explaining complex data insights in simple terms. Use clear examples to illustrate your points, and ensure you can articulate the value of your analysis.

✨Demonstrate Collaboration Skills

Highlight your experience working with cross-functional teams. Be ready to share examples of how you've collaborated with others to understand their data needs and how you provided analytical support to drive business initiatives.

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