Data Scientist - Product Operations
Next.com
Office
Leicester, Leicestershire, United Kingdom
Full Time
About The Role:
Product Operations is a team that thrives on challenge - are you seeking a role where no two days are the same? We’re looking for talented individuals who love to solve problems, analyse data and find better ways of doing things to drive real business value.
From Data Scientists, Data Engineers, Data Analysts and Product Owners, who define and scope our systems, to Operational and Merchandising roles; our team is a diverse collection of highly motivated, innovative people.
We play a crucial role at the heart of NEXT operations and work on exciting projects at the forefront of strategic vision for a retail business at the top of its game.
Overview
You will play a key role in producing detailed analysis to gain insights and building models that will make predictions allowing the business to make better decisions. The role is office based working from our Enderby head office.
Data Collation
- You will use your domain knowledge to collate and cleanse data from multiple sources.Data Analysis
- You will interrogate datasets using various techniques to identify patterns that drive business decisions.Reporting
- You will create tailored reports and visualisations to present your findings effectively to relevant stakeholders.Modelling
- Your predictive models, covering areas like future sales and returns rates, will directly influence key business decisions, including stock purchasing levels and pricing strategies.
- Stock Optimisation
Determine the most effective strategies for stock allocation, replenishment, and balancing to optimise the available inventory.
Networking
- To build, maintain and grow relationships with all relevant internal and external stakeholders. Giving you access to the people required to deliver your personal and business goals.
- Knowledge Optimisation
Seek, enable and facilitate learning opportunities. Support colleagues by sharing knowledge and understanding.
About You:
Imagine being the driving force behind transformative business decisions, fuelled by your unwavering passion for data and interest in artificial intelligence (AI). You thrive on diving deep into analysis, extracting insights that illuminate the path forward.
Your enthusiasm knows no bounds, and you're not one to sit back and wait for opportunities to come knocking. Proactive and self-aware, you understand the power of initiative and seize every chance to make an impact.
But it's not just about numbers and algorithms for you. You're a true people person, relishing the art of relationship building. Whether it's forging connections with internal teams, external stakeholders, or your peers, you excel at fostering collaborative environments where ideas flourish.
Communication is your superpower. You have a knack for distilling complex processes into easily digestible insights, effortlessly bridging the gap between technical jargon and layman's terms. Your ability to convey a simplified view to both technical and non-technical audiences sets you apart.
In the whirlwind of tasks and projects, you're the calm amidst the storm. Highly organised and adaptable, you navigate through priorities with the finesse of a seasoned conductor. Time management isn't just a skill for you—it's an art form.
You hold a degree in a numerical based subject, a testament to your dedication to continuous learning and growth. And your journey has led you through the realms of data or retail operations, honing your expertise and shaping your perspective.
You have previous experience with SQL, Python or Azure cloud software (including Databricks, Azure Data Lake etc).
Ideal, but not necessary:
- Understanding of Machine Learning techniques.
- Experience with data visualisation tools e.g. PowerBI, SSRS, Tableau.
- Familiarity with Google Apps, Gmail, Drive, Sheets.
The Team
The Data Science & Stock Optimisation team is responsible for investigating ways to maximise profit and optimise stock levels through the use of statistical modelling, data analysis and machine learning methods.
Next steps
Please submit your CV and a covering letter explaining why you are interested in working for Next and why you are applying for this role specifically.
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