At a Glance
- Tasks: Lead the SAP Data & Analytics portfolio and promote innovative offerings.
- Company: Join a forward-thinking tech company focused on data solutions.
- Benefits: Competitive salary, flexible working options, and opportunities for professional growth.
- Other info: Dynamic role with significant impact on business strategy and customer engagement.
- Why this job: Shape the future of data analytics and work with top-tier clients.
- Qualifications: 10+ years in SAP Analytics with proven leadership and communication skills.
The predicted salary is between 75600 - 92400 £ per year.
Job description
Develop and Manage the SAP Data & Analytics portfolio which includes Atos differentiated offerings for SAP Business Data Cloud, Data Sphere, SAP Analytics Cloud, Databricks, Snowflake as well as offerings for Data Management etc.
Key Responsibilities
- Actively promote the offerings into the GEOs.
- Run regular sales enablement workshops.
- Assist with pre-sales and bids in GEOs.
- Prepare and publish blogs and whitepapers.
- Actively engage with senior leaders in key customers to promote offerings and embed new features requested by customers
- Key Requirements
- At least 10 years experience as an SAP Analytics Consultant
- At least 5 full BW/4HANA implementations or migrations
- Had responsibility for the development of offerings, go to market strategy etc.
- Certified SAP Business Data Cloud, Datasphere, SAP Analytics Cloud
- Certified in at least 1 other SAP discipline - can be functional or technical or project management
- Published at least 1 white paper or blog in the last 12 months
- Excellent written and oral communications
- Experience working with C-Suite stakeholders
SAP Data & Analytics Portfolio Lead in Oxford employer: Atos
Atos is an excellent employer for Senior Full-Stack Engineers, offering a dynamic work culture that fosters innovation and collaboration. With a strong emphasis on employee growth, you will have access to continuous learning opportunities and the chance to mentor fellow engineers, all while working in a cutting-edge environment that values your contributions to scalable AI systems.
StudySmarter Expert Advice🤫
We think this is how you could land SAP Data & Analytics Portfolio Lead in Oxford
✨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 Atos!
✨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 SAP Data & Analytics Portfolio Lead at Atos.
✨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 Atos.
✨Apply Directly through Our Website
When you find a suitable opening like SAP Data & Analytics Portfolio Lead at Atos, 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 SAP Data & Analytics Portfolio Lead in Oxford
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 Atos, 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 Atos. 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 Atos
✨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 Atos!
✨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.
