Python Data Analyst - Quality & Modeling Support in Glasgow

Python Data Analyst - Quality & Modeling Support in Glasgow

Glasgow Full-Time 56250 - 68750 £ / year (est.) No working from home possible
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At a Glance

  • Tasks: Conduct quality control analyses and support data investigations using Python.
  • Company: Leading data insights company prioritising mental health and well-being.
  • Benefits: Full-time permanent position with opportunities for growth and development.
  • Other info: Dynamic work environment focused on innovation and collaboration.
  • Why this job: Join a diverse team and contribute to cutting-edge data projects.
  • Qualifications: Strong numerical and analytical skills, proficiency in Python, and excellent communication.

The predicted salary is between 56250 - 68750 £ per year.

A leading data insights company in Glasgow seeks a Data Analyst with a strong understanding of numerical and analytical skills.

The ideal candidate will support data scientists by conducting quality control analyses and data investigations, requiring proficiency in Python and excellent communication.

Join our diverse team where mental health and well-being are prioritized.

This full-time permanent position offers the opportunity to contribute to cutting-edge data projects. #J-18808-Ljbffr

Python Data Analyst - Quality & Modeling Support in Glasgow employer: Arsenault

As an Office Administrator in our flagship Mayfair office, you will be part of a dynamic and supportive work culture that values initiative and creativity. We offer excellent growth opportunities within the finance industry, alongside a commitment to employee development and a vibrant environment where your contributions are recognised. Join us to not only enhance your skills but also to play a key role in shaping the office experience for both staff and guests worldwide.

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Contact Details:

Arsenault Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Python Data Analyst - Quality & Modeling Support in Glasgow

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 Arsenault!

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 Python Data Analyst - Quality & Modeling Support at Arsenault.

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 Arsenault.

Apply Directly through Our Website

When you find a suitable opening like Python Data Analyst - Quality & Modeling Support at Arsenault, 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 Python Data Analyst - Quality & Modeling Support in Glasgow

Numerical Skills
Analytical Skills
Quality Control Analysis
Data Investigation
Proficiency in Python
Communication Skills
Data Analysis

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 Arsenault, 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 Arsenault. 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 Arsenault

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 Arsenault!

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.