At a Glance
- Tasks: Lead the design and deployment of vendor data solutions in a global transformation programme.
- Company: Join Mars Inc., a purpose-driven company with a commitment to innovation.
- Benefits: Competitive salary, bonus, and access to best-in-class learning at Mars University.
- Other info: Collaborate with diverse teams and enjoy excellent career growth opportunities.
- Why this job: Be a global expert in vendor data management and make a real impact.
- Qualifications: Bachelor's degree or 8+ years of relevant experience in data management.
The predicted salary is between 60000 - 80000 £ per year.
Mars Inc. is undertaking a global transformation program delivering a standard core of best practice processes and systems across its Enterprise and segment divisions. This Vendor Data Domain Lead role serves to represent the Shared Template, the global ERP master data design and associated maintenance process design and technical deployment. This role will work with the Global Process Owners, business process subject matter experts and peer roles in other segments to design and deploy world class End to End data solutions.
What are we looking for?
- Bachelor's degree in a relevant business function or significant experience (8yrs+) in relevant functional area
- Comprehensive understanding of Mars vendor data, related attributes, and uses (5+ yrs)
- Previous experience with Mars procurement transformation projects, preferably experience in SAP implementation, data analysis, and data conversion
- General understanding of SAP Material Management (MM) module
- Proficiency working with and analysing complex datasets; analysing data, building Excel PivotTables, and identifying trends and patterns to support data-driven decisions
- Master data management CRUD (create, read, update, delete) process experience
- Data quality and cleansing experience
- SAP data conversion experience
- Strong written and verbal communication skills to present findings and coordinate with various partner teams
- Process governance experience
- Cross team collaboration and problem solving
What will be your key responsibilities?
- Process knowledge: The Vendor Data Domain Lead is a global expert on vendor master data and how that data is managed through the Edge and ERP systems. The role needs to partner with segment and Corporate function teams to ensure a clear understanding of global processes to represent the segment as the global data process champion for the related functional areas.
- Solution Design: The role partners within the various segment, as well as with Enterprise teams, on vendor data design and related software decisions. The role participates with the cross functional segment and MGS teams, solution architects, and Business Integration partners on solution design to ensure a clean core vendor master data model while enhancing operational capability and enabling process simplification, aligned with Mars’ strategic direction for master data management.
- Solution Deployment: The role will be accountable for the deployment of the vendor master data design and associated master data management solution in the global markets and will partner with the local deployment teams to ensure a consistent and successful deployment (go-live and stabilization).
What can you expect from Mars?
- Work with diverse and talented Associates, all guided by the Five Principles.
- Join a purpose driven company, where we’re striving to build the world we want tomorrow, today.
- Best-in-class learning and development support from day one, including access to our in-house Mars University.
- An industry competitive salary and benefits package, including company bonus.
Data Domain Lead employer: TieTalent
Mars Inc. is an exceptional employer, offering a dynamic work environment in Slough, England, where you can collaborate with diverse and talented associates committed to making a positive impact. With a strong focus on employee development through Mars University and a competitive salary and benefits package, you will have ample opportunities for growth while contributing to innovative data solutions that drive the company's global transformation efforts.
StudySmarter Expert Advice🤫
We think this is how you could land Data Domain Lead
✨Get Involved in Data Science Meetups
Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like TieTalent!
✨Show Off Your Projects
Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Data Domain Lead at TieTalent.
✨Leverage Professional Networks
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 TieTalent.
✨Apply Directly through Our Website
When you find a suitable opening like Data Domain Lead at TieTalent, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!
We think you need these skills to ace Data Domain Lead
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 TieTalent, 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 TieTalent. 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 TieTalent
✨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 TieTalent!
✨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.