At a Glance
- Tasks: Support research on UK housing and planning through data analysis and project collaboration.
- Company: Join the University of Warwick's innovative CAGE research centre.
- Benefits: Competitive salary, valuable research experience, and potential for career advancement.
- Other info: Fixed-term contract for 18 months with opportunities to work closely with leading academics.
- Why this job: Make a real impact on housing policy while gaining skills in Big Data and quantitative analysis.
- Qualifications: Masters in Economics preferred; exceptional candidates with a bachelor's may be considered.
The predicted salary is between 31236 - 34610 £ per year.
Duration: Fixed-term contract for 18 months
CAGE is an established research centre based in the Department of Economics at the University of Warwick, and has recently been awarded £7.1 million by the Economic and Social Research Council (ESRC) to continue its research programme for the next five years.
Project: UK Housing and Planning System
The Co‑leaders of this project are Dr Nikhil Datta and Dr Amrita Kulka, both assistant professors at the Department of Economics at the University of Warwick, undertaking research to generate rigorous quantitative evidence related to planning in the UK, develop policy recommendations, and communicate findings transparently to policy, media and civil society stakeholders.
In the face of plummeting housing affordability in the UK, the overall project examines several dimensions of the UK housing and planning system, with several sub‑projects addressing different policy‑relevant questions.
As a Research Assistant, you will undertake research to contribute to and support the work of Dr Datta and Dr Kulka. This job includes a variety of tasks providing excellent preparation for doctoral programmes in applied economics or a career in quantitative analysis of public policies.
The role will primarily involve quantitative analysis of our newly constructed data on planning documents combined with data on housing construction, search and price information from a housing search platform, banking and credit card data, and other data that vary depending on the focus of a given sub‑project. You will also be learning how to work with Big Data through cleaning, processing, and validation, as well as combining data from various sources.
Additionally, you will contribute to developing research designs, preparing presentations for a variety of audiences (academic to policy‑oriented), and drafting academic research papers.
About You
We require an individual who has an interest in the research area, who is pro‑active and willing to work as part of a team. The Research Assistant will be expected to assist with the construction, cleaning, manipulating and analysis of Big Data. They will also conduct reviews of existing literature, datasets, and policy documents and work closely with Dr Kulka and Dr Datta throughout to disseminate project outcomes and draft presentations, reports, and academic papers.
You will have completed a masters degree in Economics by the start date. In exceptional cases we might consider a candidate with a completed bachelors degree.
£31,236 to £34,610 per annum
Research Assistant (CAGE) (111746-0626) in Coventry employer: Economicsnetwork
The University of Warwick offers an exceptional work environment for the Research Assistant role at CAGE, where you will be part of a dynamic team dedicated to impactful research on the UK housing and planning system. With a strong emphasis on employee growth, you will gain invaluable experience in quantitative analysis and Big Data, while contributing to meaningful projects that influence policy and society. The collaborative culture fosters innovation and provides opportunities for professional development, making it an ideal place for aspiring economists and researchers.
StudySmarter Expert Advice🤫
We think this is how you could land Research Assistant (CAGE) (111746-0626) in Coventry
✨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 Economicsnetwork!
✨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 Research Assistant (CAGE) (111746-0626) at Economicsnetwork.
✨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 Economicsnetwork.
✨Apply Directly through Our Website
When you find a suitable opening like Research Assistant (CAGE) (111746-0626) at Economicsnetwork, 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 Research Assistant (CAGE) (111746-0626) in Coventry
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 Economicsnetwork, 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 Economicsnetwork. 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 Economicsnetwork
✨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 Economicsnetwork!
✨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.
