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Datatech

Retail Geospatial Data Analyst

Datatech Tring
32 - 40 hour


Show Recently closed jobs

    Datatech

    Retail Geospatial Data Analyst

    Datatech Tring
    32 - 40 hour
    Status Open
    Apply now

    Apply on the employer's website


    What we ask

    Education

    No minimum education required

    What we offer

    Hours
    32 to 40 hours per week
    Employment type
    permanent

    Job description

    Graduate Geospatial Data Analyst - Entry Level Role - Hertfordshire - Hertfordshire Office based - Salary up to £30,000 Depending on skills - J13148

    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. Seeking a graduate who has strong analytical foundations, strong judgement and the appetite to develop into a broader retail analytics and geospatial consulting role.

    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! If you have a friend or colleague who would be interested in this role, please refer them to us. For each relevant candidate that you introduce to us (there is no limit) and we place, you will be entitled to our general gift/voucher scheme.

    Datatech is one of the UK's leading recruitment agencies in the field of analytics and host of the critically acclaimed event, Women in Data. For more information, visit our website: (url removed)
    Apply now

    Apply on the employer's website

    Apply now

    Apply on the employer's website


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