Remote Power BI Data Analyst: Marketing Insights & Modeling in Oxford

Remote Power BI Data Analyst: Marketing Insights & Modeling in Oxford

Oxford Full-Time 40200 - 57533 £ / year (est.) Working from home possible
Wiley

At a Glance

  • Tasks: Create impactful data models and reports to enhance marketing strategies.
  • Company: Join Wiley, a leader in innovative marketing solutions.
  • Benefits: Competitive salary, fully remote work, and opportunities for professional growth.
  • Other info: Be part of a dynamic team focused on strategic decision-making.
  • Why this job: Make a real difference in marketing with your data skills.
  • Qualifications: 4+ years in Data Modelling, strong Power BI and SQL skills.

The predicted salary is between 40200 - 57533 £ per year.

Wiley is seeking a skilled Data Analyst with Power BI expertise to join their marketing team. This fully remote position requires a methodical thinker who will develop important data models for strategic decision-making.

Applicants should have over four years of experience in Data Modelling and strong skills in Power BI and SQL. The role involves creating reports that optimize marketing campaigns and contribute to data governance.

The salary range is between 40,200 GBP and 57,533 GBP.

Remote Power BI Data Analyst: Marketing Insights & Modeling in Oxford employer: Wiley

Wiley is an exceptional employer that values innovation and collaboration, offering a fully remote work environment that promotes flexibility and work-life balance. With a strong focus on employee growth, we provide ample opportunities for professional development and skill enhancement, particularly in data analytics and marketing insights. Join us to be part of a dynamic team where your contributions directly impact strategic decision-making and drive meaningful results.

Wiley

Contact Details:

Wiley Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Remote Power BI Data Analyst: Marketing Insights & Modeling in Oxford

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 Wiley!

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 Remote Power BI Data Analyst: Marketing Insights & Modeling at Wiley.

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 Wiley.

Apply Directly through Our Website

When you find a suitable opening like Remote Power BI Data Analyst: Marketing Insights & Modeling at Wiley, 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 Remote Power BI Data Analyst: Marketing Insights & Modeling in Oxford

Power BI
Data Modelling
SQL
Data Analysis
Report Creation
Marketing Insights
Data Governance

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 Wiley, 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 Wiley. 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 Wiley

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 Wiley!

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.