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For Companies At a Glance
- Tasks: Join a dynamic team to analyse data and create impactful solutions.
- Company: A leading consultancy focused on data-driven growth and innovation.
- Benefits: Competitive salary, collaborative environment, and opportunities for professional development.
- Why this job: Make a real impact with your work while developing your skills in a supportive setting.
- Qualifications: 2:1 degree in Computer Science, Mathematics, or related field; experience with data visualisation tools.
- Other info: Opportunity to work on diverse projects and see immediate results from your contributions.
The predicted salary is between 20000 - 26000 £ per year.
A consultancy business is looking for someone who is truly passionate about data. Someone who will work on a variety of projects, assisting the business to improve productivity, commercial optimisation and growth. Reporting to the Head of Data Science you will join a busy, friendly and dynamic team using numbers and facts to make key recommendations, such as which business case to fund, which company we should buy next or which strategic partnership/venture to progress. They are at the forefront of their industry, with an appetite for growth and innovation, constantly looking to do things better and faster, using data-driven decisions. You will make an impact and quickly see the results of your work.
Responsibilities
- Aid in the migration and analysis of data and the creation of one, unified data set giving one point of truth
- Clear understanding of business requirements and propose/implement complete solutions
- Create easy to understand and clear data visualisations
- Creation and maintenance of machine learning models
- Create and undertake testing procedures/policies using test-driven development methodologies
- Query writing/building
- System contingency planning and implementations
Essential Requirements
- A mathematics/computer science background with knowledge of numerous machine learning models - some alternative degrees will be considered
- Experience with data visualisation tools (Power BI etc.)
- Exceptional Microsoft Office skills
- Detail orientation with structured thinking
- A problem solver with the ability to multi-task
- A top performer who is comfortable in an unstructured environment which values initiative, creativity, maturity, poise and strong analytical skills
- At least a 2:1 degree in Computer Science, Mathematics, Software Engineering or similar
- Microsoft SQL Server Experience
- R & Python Experience
- Creativity and an eye for branding
Please note due to the large volume of applications we receive for these roles, if we have not contacted you within 7 days then unfortunately your application hasn’t been successful, however we may contact you regarding other roles. We’re sorry we can’t contact you directly, but we wish you all the best in your job search.
Graduate Data Scientist - Coventry employer: Agility Resoucing
Contact Detail:
Agility Resoucing Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate Data Scientist - Coventry
✨Tip Number 1
Familiarise yourself with the latest trends in data science and machine learning. Being able to discuss recent advancements or tools during your interview can demonstrate your passion and commitment to the field.
✨Tip Number 2
Showcase your experience with data visualisation tools like Power BI. If you have any personal projects or case studies, be ready to discuss how you used these tools to derive insights from data.
✨Tip Number 3
Prepare to discuss your problem-solving approach. Think of specific examples where you've tackled complex data challenges, as this will highlight your analytical skills and ability to thrive in an unstructured environment.
✨Tip Number 4
Network with professionals in the data science field, especially those who work in consultancy. Engaging with them on platforms like LinkedIn can provide valuable insights and potentially lead to referrals.
We think you need these skills to ace Graduate Data Scientist - Coventry
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the job description. Emphasise your background in mathematics or computer science, and any experience with machine learning models and data visualisation tools.
Craft a Compelling Cover Letter: Write a cover letter that showcases your passion for data and your problem-solving abilities. Mention specific projects or experiences that demonstrate your analytical skills and creativity, and explain why you want to work for this consultancy.
Showcase Technical Skills: In your application, clearly outline your proficiency in programming languages like R and Python, as well as your experience with Microsoft SQL Server. Providing examples of how you've used these skills in past projects can strengthen your application.
Highlight Soft Skills: Don't forget to mention your soft skills such as attention to detail, structured thinking, and the ability to multi-task. These are essential for thriving in a dynamic team environment, so provide examples of how you've demonstrated these traits in previous roles.
How to prepare for a job interview at Agility Resoucing
✨Show Your Passion for Data
Make sure to express your genuine enthusiasm for data during the interview. Discuss any personal projects or experiences that highlight your passion and how you’ve used data to solve problems or make decisions.
✨Demonstrate Your Technical Skills
Be prepared to discuss your experience with machine learning models, SQL, R, and Python. You might be asked to solve a technical problem on the spot, so brush up on your coding skills and be ready to showcase your knowledge.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities in real-world scenarios. Think of examples where you've successfully tackled challenges using data analysis and visualisation, and be ready to explain your thought process.
✨Ask Insightful Questions
At the end of the interview, ask questions that show your interest in the company’s projects and future direction. Inquire about their data-driven decision-making processes or how they measure the success of their initiatives to demonstrate your engagement.