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- Tasks: Join a team to create impactful reports and dashboards for business intelligence decisions.
- Company: Work with a client implementing SAP S/4HANA Public Cloud and SAP Analytics Cloud.
- Benefits: Enjoy a 12-month contract with opportunities for continuous learning and collaboration.
- Why this job: Be part of a dynamic team, enhancing your skills in data analysis and reporting.
- Qualifications: Degree in Computing or equivalent; experience in data analysis and ETL processes required.
- Other info: Must attain National Security Vetting to SC level; familiarity with GDPR is essential.
The predicted salary is between 36000 - 60000 £ per year.
SAP Data Scientist
12-month contract
SystemsAccountants are currently working with a client implementing SAP S/4HANA Public Cloud and SAP Analytics Cloud, seeking a Data Scientist to join the team, collaborating with key stakeholders to create impactful reports and dashboards to enable key business intelligence decisions. The successful candidate will work closely with the database administrator to ensure data is clean and available, allow meaningful reports to be made available efficiently, and ensure a single source of truth behind all data decisions.
Role Responsibilities
- Data Warehousing: Collaborate with senior developers to design, develop, and maintain reports, dashboards, and visualizations that effectively communicate complex data insights.
- Data Analysis: Work closely with business stakeholders to understand their reporting requirements and translate them into effective data models and visualizations.
- Data Integration: Assist in integrating data from various sources into DW using appropriate Extract, Transfer and Load (ETL) processes, ensuring data quality and integrity.
- Transfer current Data Warehouse reports into SAP Analytics Cloud (SAC).
- Report Optimization: Optimize existing reports and dashboards for improved performance, usability, and user experience.
- Testing and Troubleshooting: Conduct thorough testing of reporting solutions (SAC) to identify and resolve any issues or bugs, ensuring accuracy and reliability of the data.
- Documentation: Document data models, report specifications, and development processes to ensure clear communication and knowledge sharing within the team.
- Collaboration: Collaborate with cross-functional teams, including business analysts, data engineers, and stakeholders, to gather requirements and ensure successful project outcomes.
- Continuous Learning: Stay up to date with the latest trends and best practices in DW development and business intelligence to enhance technical skills and contribute to ongoing process improvements.
Role Requirements
- Degree in Computing subject or equivalent.
- Certification in Data Warehousing and related technologies is a plus.
- Must be able to attain and hold National Security Vetting to a minimum SC level.
- Experience in data analysis, modelling, and management.
- Prior experience in developing analytical data models and ETL (Extract, Transform, Load) processes.
- Adept at designing, implementing, and optimizing data models to drive insightful analytics and support decision-making. Skills in building and managing ETL workflows to ensure the efficient and accurate movement of data across systems.
- Experience in SAP Data Tools – particularly SAP Analytics Cloud and SAP DataSphere. Proficiency in leveraging these tools to develop, manage, and optimize data models, analytics, and reporting solutions.
- Experience in managing priorities and stakeholders, with skills in balancing multiple tasks and projects simultaneously, ensuring that critical deadlines are met.
- The ideal candidate should have prior experience working with protected and sensitive data, such as ITAR (International Traffic in Arms Regulations) data.
- Experience working with MRP (Material Requirements Planning) and/or ERP (Enterprise Resource Planning) generated data.
- Ability to communicate complex data insights to non-technical stakeholders and collaborate with cross-functional teams.
- Strong working knowledge of SQL and DAX. Familiarity with VBA, PowerShell, and Python is a plus.
- Strong understanding & proficiency in data modelling, statistical analysis, and predictive modelling.
- An understanding of data privacy laws and regulations such as GDPR is essential.
- Knowledge of industry-standard security protocols and frameworks, such as ISO 27001.
- Proficiency in generating regulatory reports and documentation as required by relevant authorities.
- The ideal candidate would have experience in using monitoring tools such as SPLUNK, Datadog, or New Relic.
- Understanding of business intelligence concepts and the ability to translate business needs into data-driven insights.
Seniority level
Mid-Senior level
Employment type
Contract
Job function
Information Technology
Industries
Manufacturing and Information Services
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SAP Data Scientist employer: SystemsAccountants
Contact Detail:
SystemsAccountants Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land SAP Data Scientist
✨Tip Number 1
Familiarise yourself with SAP Analytics Cloud and SAP DataSphere, as these tools are crucial for the role. Consider exploring online tutorials or courses to enhance your skills and demonstrate your commitment to mastering these platforms.
✨Tip Number 2
Network with professionals in the data science and SAP communities. Attend relevant meetups or webinars to connect with others in the field, which can provide insights into the role and potentially lead to referrals.
✨Tip Number 3
Brush up on your SQL and DAX skills, as these are essential for data modelling and analysis. Practice by working on sample datasets to improve your proficiency and prepare for technical discussions during interviews.
✨Tip Number 4
Stay updated on the latest trends in data warehousing and business intelligence. Follow industry blogs or join forums to engage with current topics, which will help you speak knowledgeably about innovations during your interview.
We think you need these skills to ace SAP Data Scientist
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in data analysis, modelling, and management. Emphasise your proficiency with SAP Analytics Cloud and any ETL processes you've worked on.
Craft a Compelling Cover Letter: In your cover letter, explain why you're interested in the SAP Data Scientist role specifically. Mention how your skills align with the responsibilities outlined in the job description, such as report optimisation and collaboration with cross-functional teams.
Showcase Technical Skills: Clearly list your technical skills, especially those mentioned in the job description like SQL, DAX, and familiarity with Python. Provide examples of how you've used these skills in past projects to solve problems or improve processes.
Highlight Continuous Learning: Mention any recent courses, certifications, or self-study you've undertaken related to data warehousing and business intelligence. This shows your commitment to staying updated with industry trends and best practices.
How to prepare for a job interview at SystemsAccountants
✨Showcase Your Technical Skills
Be prepared to discuss your experience with SAP Analytics Cloud and other relevant data tools. Highlight specific projects where you've successfully implemented ETL processes or developed analytical data models, as this will demonstrate your technical proficiency.
✨Understand the Business Context
Research the company and its industry to understand their specific data needs. Be ready to explain how your skills can help them make data-driven decisions, especially in relation to manufacturing and information services.
✨Prepare for Scenario-Based Questions
Expect questions that assess your problem-solving abilities. Prepare examples of how you've tackled challenges in data analysis, report optimisation, or collaboration with stakeholders, as these will showcase your practical experience.
✨Communicate Clearly with Non-Technical Stakeholders
Practice explaining complex data insights in simple terms. This is crucial, as you'll need to collaborate with cross-functional teams and convey your findings to those who may not have a technical background.
