At a Glance
- Tasks: Analyse geospatial data to help retailers optimise their physical spaces and make data-driven decisions.
- Company: Join a leading international retail design consultancy with a focus on innovation.
- Benefits: Salary up to £30,000, career growth, and opportunities to work with cutting-edge tools.
- Other info: Collaborative culture with opportunities for professional development and a fantastic referral scheme.
- Why this job: Make a real impact in retail analytics while developing your skills in a dynamic environment.
- Qualifications: Degree in a quantitative field and strong skills in Python and SQL.
The predicted salary is between 30000 - 30000 £ per year.
Join an international retail design and insight consultancy, helping retailers and consumer brands make better decisions about physical retail space using data. Combining consumer behaviour, geospatial analysis, retail planning expertise and commercial insight to support data driven decisions on category performance, space optimisation and much more.
A brand-new opportunity for a numerical graduate to bring drive and curiosity to join the analytics and consulting team. In this role you'll work on real world retail and location problems, using tools such as Python, SQL and geospatial data to turn historic data into clear insights, models and client ready recommendations. A key part of your role will be to help the organisation build more repeatable workflows, code and an overall stronger analytical quality control.
Responsibilities:
- Support analytical workstreams within client projects, from data preparation through to final outputs.
- Work with datasets such as site locations, catchments, demographics, mobility data, points of interest, competitors, sales and customer data.
- Use Python and SQL to clean, join, analyse and structure data.
- Create maps, charts, dashboards, reports and presentations that explain complex analysis clearly.
- Support modelling tasks such as clustering, segmentation, site scoring, similarity matching and offer-fit analysis.
- Help validate results, sense-check model outputs and explain to a non-technical audience.
- Contribute reusable code and documentation that reduces manual rework on future projects.
- Collaborate with colleagues through GitHub, shared standards and code review.
Skills Required:
- A degree in a quantitative, analytical or spatial subject such as geography, data science, statistics, mathematics, operational research, economics, engineering, GIS, planning or a related field.
- Good Python skills, particularly for data manipulation and analysis using libraries such as pandas.
- Practical experience using SQL to query, join and transform data.
- Experience working with geospatial data, either in Python, GIS software, spatial databases or a similar analytical environment.
- Strong data cleaning skills, including working with incomplete, inconsistent or messy datasets.
- Ability to structure analysis clearly and document the steps taken.
- Good communication skills, with the ability to explain analytical outputs in plain English.
- Interest in retail, consumer behaviour, location analysis, property, mobility, networks or physical-space optimisation.
- A practical, problem-solving mindset and willingness to learn new tools and methods.
If you would like to hear more, please do get in touch. Alternatively, you can refer a friend or colleague by taking part in our fantastic referral schemes!
Retail Geospatial Data Analyst employer: Datatech Analytics
Join a dynamic international retail design and insight consultancy in Hertfordshire, where your analytical skills will directly impact the future of retail. With a strong emphasis on employee growth, you will have access to mentorship and training opportunities, fostering a collaborative work culture that values innovation and creativity. Enjoy competitive benefits, including a salary of up to £30,000, and the chance to work on real-world projects that shape the retail landscape.
StudySmarter Expert Advice🤫
We think this is how you could land Retail Geospatial Data Analyst
✨Embrace Online Competitions
Get involved in online data science competitions like Kaggle or DrivenData. These platforms not only let you showcase your skills but also help you build a portfolio that stands out to hiring companies like Datatech Analytics when you're aiming for that entry-level role.
✨Join Data Science Meetups
Look for local data science meetups or workshops happening in your area. These are perfect for connecting with industry professionals and fellow newbies, giving us the chance to learn the ropes and get our foot in the door at companies like Datatech Analytics.
✨Networking Through University Career Services
Don't forget to leverage your university's career services! They often have exclusive internships and networking events specifically for entry-level data science positions. This is a golden opportunity to meet recruiters from companies like Datatech Analytics.
✨Spotlight Your Skills Online
Create a strong online presence by sharing your projects and insights on platforms like GitHub or LinkedIn. Make sure to apply directly through Datatech Analytics’s career page, where your unique skills can shine in their entry-level data science openings!
We think you need these skills to ace Retail Geospatial Data Analyst
Some tips for your application 🫡
Show Off Your Data Skills:As you're aiming for an entry-level data science role at Datatech Analytics, don't forget to highlight your proficiency in programming languages like Python or R. Dive into your CV and mention any relevant projects or coursework that demonstrate your data analysis skills or machine learning knowledge.
Include Relevant Projects:If you've done any data-related projects, whether in your studies or during a personal quest, showcase them in a portfolio. This gives us a tangible sense of your capabilities and shows your hands-on experience with data manipulation, visualisation, or model building.
Tailor Your Cover Letter:When crafting your cover letter, make sure to express your enthusiasm for data science and how this role at Datatech Analytics aligns with your career goals. Consider sharing why you’re drawn to data-driven decision-making and how you see yourself growing in this field.
Show Your Curiosity:In the data science world, curiosity is key! Mention any online courses or certifications you've pursued that complement your studies. This could be anything from a statistics certification to a data visualisation workshop. It shows us you're serious about learning and growing in this field.
How to prepare for a job interview at Datatech Analytics
✨Brush Up on Your Statistics
For a data science role, the interview may involve some statistical questions or problems. Make sure you're comfortable with concepts like probability, distributions, and hypothesis testing. This will not only help you answer questions but also show your analytical thinking.
✨Get Hands-On with Tools
Familiarise yourself with popular data science tools like Python, R, and SQL. If you're asked about specific projects, be ready to discuss the tools you used and how they contributed to your analysis. Showing that you not only know the theory but can apply it is essential!
✨Showcase Relevant Projects
As an entry-level candidate, your portfolio is crucial. Bring along examples of data projects you've worked on, whether during your studies or personal projects. Discuss the challenges you faced and how you overcame them, highlighting your problem-solving skills.
✨Prepare for Case Studies
Entry-level interviews in data science often include case studies where you'll have to analyse a dataset or solve a problem on the spot. Try out some practice case studies beforehand, so you're not caught off guard. It's all about displaying your thought process and how you tackle data-driven challenges!
