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- Tasks: Support a project integrating predictive analysis for cycling products supply chain management.
- Company: Edinburgh Napier University is a leading institution focused on applied research and employability.
- Benefits: Enjoy 46 days annual leave, flexible working, and professional development opportunities.
- Why this job: Make an impact in cycling supply chains while growing your academic and industry network.
- Qualifications: Masters in Analytics, Data Science, or related fields; experience with forecasting models required.
- Other info: Fixed-term contract for 7 months; full-time role with no sponsorship for international workers.
The predicted salary is between 28800 - 48000 £ per year.
Research Assistant – Forecasting and Scenario Analysis Join to apply for the Research Assistant – Forecasting and Scenario Analysis role at Edinburgh Napier University . Pay Range This range is provided by Edinburgh Napier University. Your actual pay will depend on your skills and experience — discuss with your recruiter for more details. About the University Edinburgh Napier Business School is dedicated to empowerment, enterprise, and employability. It is one of Scotland’s largest Business Schools, with a focus on applied research that is policy and practice relevant both nationally and internationally. The Role We are recruiting a Research Assistant to support a project integrating predictive analysis of sales and stock data into The Bicycle Association’s Market Data Service (MDS), aimed at enhancing cycling products supply chain management. This role offers an excellent opportunity for early-career academics to support a high-impact project influencing stock decisions based on demand variability. Responsibilities include developing and implementing forecasting models (preferably related to inventory or supply chain management), analyzing data, and creating user-facing tools to communicate demand scenarios for stock planning. You will collaborate with stakeholders to understand data, forecast needs, and develop actionable insights, contributing to your professional growth and network expansion in academia and industry. Candidate Requirements Masters in a quantitative discipline such as Analytics, Data Science, Statistics, Mathematics, or related fields. Experience with forecasting models, especially in inventory or supply chain contexts. Strong knowledge of statistical forecasting techniques and proficiency in Python (Pandas, NumPy, Scikit-learn, Prophet) or R. Excellent analytical and problem-solving skills with the ability to interpret complex data. Additional Details For full duties, click here. Benefits include 46 days annual leave, a generous pension scheme, flexible working, and professional development opportunities. Contract: Fixed-term, 7 months. Hours: Full-time, 35 hours/week. Note: The university cannot sponsor international workers on the Skilled Worker visa; applicants must have the right to work in the UK. We are committed to diversity and inclusion, holding various awards and accreditations. Job Details Seniority level: Associate Employment type: Full-time Job functions: Research, Finance, and related fields Industry: Higher Education #J-18808-Ljbffr
Research Assistant – Forecasting and Scenario Analysis employer: Edinburgh Napier University
Contact Detail:
Edinburgh Napier University Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Assistant – Forecasting and Scenario Analysis
✨Tip Number 1
Familiarise yourself with the specific forecasting models mentioned in the job description, such as those related to inventory and supply chain management. This will not only help you understand the role better but also allow you to engage in meaningful conversations during interviews.
✨Tip Number 2
Network with professionals in the field of data science and analytics, especially those who have experience in supply chain management. Attend relevant workshops or webinars to expand your knowledge and make connections that could lead to valuable insights about the role.
✨Tip Number 3
Brush up on your Python skills, particularly with libraries like Pandas, NumPy, and Scikit-learn. Consider working on personal projects or contributing to open-source projects that involve forecasting to demonstrate your proficiency and passion for the subject.
✨Tip Number 4
Prepare to discuss how you can contribute to the project’s goals by developing user-facing tools for stock planning. Think about examples from your past experiences where you successfully communicated complex data insights to non-technical stakeholders.
We think you need these skills to ace Research Assistant – Forecasting and Scenario Analysis
Some tips for your application 🫡
Understand the Role: Read the job description thoroughly to grasp the responsibilities and requirements of the Research Assistant position. Highlight your relevant experience in forecasting models and data analysis.
Tailor Your CV: Customise your CV to reflect your skills in quantitative disciplines, particularly focusing on your experience with Python or R, and any relevant projects related to inventory or supply chain management.
Craft a Compelling Cover Letter: Write a cover letter that connects your background in analytics or data science to the specific needs of the role. Emphasise your analytical skills and your ability to develop actionable insights from complex data.
Highlight Collaborative Experience: Mention any previous experiences where you collaborated with stakeholders or worked in teams. This is crucial as the role involves working closely with others to understand data and forecast needs.
How to prepare for a job interview at Edinburgh Napier University
✨Showcase Your Technical Skills
Make sure to highlight your experience with forecasting models and statistical techniques during the interview. Be prepared to discuss specific projects where you've used Python or R, especially in relation to inventory or supply chain management.
✨Understand the Role's Impact
Familiarise yourself with how the role contributes to The Bicycle Association’s Market Data Service. Being able to articulate how your work will influence stock decisions based on demand variability will demonstrate your understanding of the project's significance.
✨Prepare for Data Analysis Questions
Expect questions that assess your analytical and problem-solving skills. Brush up on interpreting complex data sets and be ready to explain your thought process when developing forecasting models or user-facing tools.
✨Engage with Stakeholders
Since collaboration is key in this role, think of examples where you've successfully worked with stakeholders. Be ready to discuss how you gathered requirements and translated them into actionable insights, as this will show your ability to communicate effectively.
