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- Tasks: Analyse data and optimise category performance in a leading tech eCommerce platform.
- Company: Join a top-tier eCommerce platform specialising in consumer goods and delivery.
- Benefits: Enjoy hybrid work, comprehensive insurance, company shares, and career growth opportunities.
- Why this job: Be part of an entrepreneurial team making impactful decisions in a dynamic environment.
- Qualifications: 3-6 years in analytics or data science; strong statistical analysis skills required.
- Other info: Opportunity to manage a Data Analyst and collaborate with various teams.
The predicted salary is between 36000 - 60000 £ per year.
Quest Search & Selection are currently partnering with a leading tech eCommerce platform specialised in consumer goods and delivery. This business offers an extensive range of products including household essentials, medication, office supplies, groceries, and even fresh prepared food!
The Data Scientist- Category Management, will develop decision support systems, analyse large datasets, and share insights to optimise category performance. You will collaborating with In-Stock Merchandising team and will manage another Data Analyst to drive NPD, category decision-making, and analysis in product buying and inventory management.
Key responsibilities of this Data Scientist – Category Management:
- Partner with the Data Team to measure and report on availability levels and their impact on revenue and order volumes.
- Collaborate with the Category and In-Stock Management teams to enhance the Stock Ordering Tool and refined buying policies.
- Deliver clear insights into the performance and value of buying policies integrated into the Stock Ordering Tool.
- Ensuring wastage target levels for expirations and availability are achieved.
- Design and evaluate experiments to optimise buying policies within Stock Ordering.
- Establish dynamic targets for availability and expirations across subcategories.
- Conduct in-depth analyses and post-implementation reviews to address challenges, uncover opportunities, and propose future experiments related to availability and expirations reporting.
Key requirements of Data Scientist – Category Management:
- Ideally having 3-6 years of experience in analytics or data science, preferably in grocery, operations, marketing or consumer products.
- Open to experience in Investment Banking as Senior Associate or VP level
- Strong understanding of statistical analysis and experiment design.
- Ideally a bachelor’s degree or similar in, Mathematics, Statistics, or a related quantitative discipline is advantageous but not essential
- Experience in developing machine learning models using advanced techniques.
- Expert proficiency in SQL and databases, with the ability to write structured and efficient queries on large data sets.
- Experience with dbt, Python or R, is a plus.
- Development experience with BI platforms such as Looker, Tableau, or Power BI.
Benefits included for Data Scientist – Category Management:
- Comprehensive medical and dental insurance.
- Company Shares /RSU
- Annual bonus
- Hybrid role – 3 days in office
- Employee discount.
- Career growth opportunities.
- Annual performance appraisal and bonus.
This is a great opportunity if you have the right skill sets to be part of an entrepreneurial team. If this role is of interest, please do apply quoting the reference no. JO-2501-114981
Data Scientist - Category Management employer: Quest Search and Selection
Contact Detail:
Quest Search and Selection Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Data Scientist - Category Management
✨Tip Number 1
Familiarise yourself with the specific tools and technologies mentioned in the job description, such as SQL, Python, and BI platforms like Tableau or Power BI. Having hands-on experience or projects showcasing your skills with these tools can set you apart during discussions.
✨Tip Number 2
Prepare to discuss your experience with statistical analysis and experiment design. Think of examples where you've successfully applied these skills to drive insights or optimise processes, as this will demonstrate your capability to contribute effectively to the team.
✨Tip Number 3
Network with professionals in the eCommerce and consumer goods sectors. Engaging with industry-specific groups on platforms like LinkedIn can provide valuable insights and connections that may help you learn more about the company culture and expectations.
✨Tip Number 4
Be ready to showcase your problem-solving skills through case studies or scenarios related to inventory management and category performance. This will highlight your analytical thinking and ability to apply data-driven solutions in real-world situations.
We think you need these skills to ace Data Scientist - Category Management
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in analytics or data science, especially in grocery, operations, or consumer products. Emphasise any experience with SQL, machine learning models, and BI platforms like Tableau or Power BI.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company. Mention specific projects or experiences that demonstrate your ability to analyse large datasets and optimise category performance.
Showcase Technical Skills: Clearly outline your technical skills in SQL, Python, R, and any experience with dbt. Provide examples of how you've used these skills in past roles to drive decision-making and improve processes.
Highlight Collaboration Experience: Since the role involves collaboration with various teams, include examples of how you've successfully worked with cross-functional teams in the past. This could be in terms of enhancing tools or driving category decisions.
How to prepare for a job interview at Quest Search and Selection
✨Showcase Your Analytical Skills
As a Data Scientist, you'll need to demonstrate your analytical prowess. Be prepared to discuss specific projects where you've used statistical analysis or machine learning techniques. Highlight how your insights led to tangible improvements in decision-making or performance.
✨Familiarise Yourself with the Company’s Products
Since the role involves optimising category performance for a tech eCommerce platform, understanding their product range is crucial. Research the types of consumer goods they offer and think about how data can enhance their inventory management and buying policies.
✨Prepare for Technical Questions
Expect questions on SQL, Python, or R, as well as your experience with BI platforms like Tableau or Power BI. Brush up on writing efficient queries and be ready to explain your approach to developing machine learning models. Practical examples will help illustrate your expertise.
✨Demonstrate Collaboration Skills
This role requires working closely with various teams, including In-Stock Merchandising. Prepare examples of how you've successfully collaborated with cross-functional teams in the past, focusing on communication and teamwork to achieve common goals.
