At a Glance
- Tasks: Ensure data quality and accuracy for product launches across multiple regions.
- Company: Join a dynamic team focused on data excellence in the ecommerce sector.
- Benefits: Competitive daily rate, remote work flexibility, and a chance to shape product data strategies.
- Other info: Opportunity for career growth in a fast-paced, collaborative environment.
- Why this job: Be a key player in launching innovative products while enhancing your data management skills.
- Qualifications: 5+ years in data management with PIM systems like InRiver or Salsify.
The predicted salary is between 30000 - 40000 £ per year.
Based: Remote, within the UK or Europe
Type: Initial full-time contract to June 2027
Salary: Up to £400 per day
We're hiring a new role on behalf of a client to support the improvement and quality of their data in the EMEA Region, as part of a wider migration programme. It is an essential requirement that you have previous experience of syndication (ETL) in InRiver or Salsify PIM systems.
In this hands-on role, you will be the key person responsible for ensuring the completeness, quality, and accuracy of data from multiple sources, supporting the timely launch of new products across multiple regions. You’ll play a critical role in QA, validating and cross-checking data across various systems, ensuring it meets the necessary standards for product launches.
Key Responsibilities- Data Validation: Ensure that all mandatory product data across core systems is complete, accurate, and up to date. Ensuring QA process is followed across ecommerce platforms.
- Data Stewardship: Coordinate with data owners to correct discrepancies in data and ensure consistency across systems.
- Problem-Solving: Identify areas where data quality can be improved and work with various teams to implement solutions.
- Stakeholder Collaboration: Communicate with stakeholders to clarify data requests and address any data-related issues, ensuring alignment with launch schedules.
- Data Tracking & Reporting: Create and manage detailed reports on product data status and product launch progress.
- Data Management Expertise: Minimum of 5 years of experience working with data management principles and data integrity concepts, including syndication in PIM InRiver or Salsify.
- Ecommerce or Retail Experience: Experience working in an ecommerce or retail environment, especially with platforms that serve multiple countries and markets.
- Tool Proficiency: Advanced skills in Excel, and other data tools to maintain and manage data inputs and outputs. This includes dashboard creation.
- Data Systems Knowledge: Familiarity with a range of data management systems.
- Data Lifecycle Understanding: Ability to manage and understand the complete lifecycle of product data from creation to launch.
- Analytical & Detail-Oriented: Strong analytical mindset with keen attention to detail and the ability to spot discrepancies or gaps in data.
- Communication Skills: Effective communication with both business and technical stakeholders, ensuring clarity in data-related discussions.
Senior Product Data Specialist (PIM) employer: Academia Group
As a Senior Product Data Specialist (PIM) with our client, you will join a dynamic and innovative team dedicated to enhancing data quality across the EMEA region. The company fosters a collaborative work culture that values employee growth, offering opportunities for professional development and skill enhancement in a remote setting. With competitive compensation and a focus on work-life balance, this role provides a meaningful chance to contribute to impactful product launches while working alongside industry experts.
StudySmarter Expert Advice🤫
We think this is how you could land Senior Product Data Specialist (PIM)
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Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Academia Group.
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We think you need these skills to ace Senior Product Data Specialist (PIM)
Some tips for your application 🫡
Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!
Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!
Craft a Tailored Cover Letter:For a full-time role at Academia Group, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.
Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Academia Group. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!
How to prepare for a job interview at Academia Group
✨Brush Up on Your Statistics
For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!
✨Showcase Your Projects
Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!
✨Get Comfortable with Python and R
Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Academia Group!
✨Prepare for Case Studies
Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.
