Project Manager - Data Analytics (Supply Chain)

Siemens Healthineers
Oxford
2 days ago
Create job alert

Join us in pioneering breakthroughs in healthcare. For everyone. Everywhere. Sustainably.


Our inspiring and caring environment forms a global community that celebrates diversity and individuality. We encourage you to step beyond your comfort zone, offering resources and flexibility to foster your professional and personal growth, all while valuing your unique contributions.


Varian Medical Systems, a Siemens Healthineers company is seeking a highly analytical, technically skilled, and results-oriented Project Manager with a Data Analytics emphasis to lead strategic data initiatives within Varian’s Supply Chain Plan & Materials organization. In this role, you will drive high-impact analytics, digital transformation, and process-improvement projects that enhance supply chain visibility, planning accuracy, operational efficiency, and overall performance. You will partner closely with cross-functional teams to convert complex data into actionable insights, streamline core planning and materials workflows, and embed a culture of data-driven decision-making across SCM Plan & Materials.


Preference is for a candidate who can be onsite 2 days/week at a Varian location


What You Will Do

  • Lead cross-functional analytics and process improvement initiatives to optimize planning, purchasing, material flow, and overall supply chain performance.
  • Analyze complex supply chain challenges using SAP data (MM, PP, MRP) and other enterprise systems to identify operational gaps, risks, and opportunities.
  • Design, automate, and optimize data pipelines and reporting workflows to improve data accuracy, consistency, and timeliness across planning and procurement activities.
  • Develop dynamic dashboards and visualizations (Power BI, Qlik Sense, etc.) to communicate performance trends, forecast accuracy, inventory health, material availability, and supplier performance.
  • Collaborate with Material Master Data, Supply Chain, Operations, Procurement, Finance, and IT partners to ensure analytics initiatives align with business objectives and digital transformation strategies.
  • Establish and maintain strong data governance practices across SAP and analytics platforms to support reliable, real-time decision-making.
  • Champion analytics adoption and data literacy, enabling planners, buyers, and leaders to leverage insights in daily operations and strategic planning.
  • Drive continuous improvement, documenting processes, standardizing data workflows, and implementing scalable solutions that enhance supply chain visibility and responsiveness.

What You Will Have

  • Bachelors degree in: Computer Science, Supply Chain, Data Analytics, or related field and 3+ years of experience OR Masters degree and 1+ years of experience
  • Proven experience in project management and data analytics within a supply chain, operations, or manufacturing environment.
  • Advanced SAP expertise in planning and purchasing processes, including MRP, BOM management, source list/Info Records, and production planning (MM, PP, related modules).
  • Track record of leading analytics and process optimization projects from concept through execution, delivering measurable improvements in performance.
  • Strong analytical and problem-solving capabilities, with the ability to translate data into actionable insights and process enhancements.
  • Proficiency with data visualization and analytics tools (Power BI, Qlik Sense) and data analysis languages/tools (SQL, VBA, Python, or R).
  • High attention to detail and strong commitment to data quality, accuracy, and governance.
  • Exceptional communication, collaboration, and stakeholder management skills, with demonstrated ability to influence across all organizational levels.

What Will Set You Apart

  • Experience in supply chain analytics, including forecasting, inventory optimization, and supplier performance measurement.
  • Experience with SAP analytics and data integration technologies (BW, HANA, or Snowflake-based data platforms).
  • Knowledge of Lean, Six Sigma, Agile, or other continuous improvement/digital transformation methodologies.
  • Experience developing and deploying machine learning or AI models to support predictive and prescriptive analytics.

#LS-OS1


The base pay range for this position is: $87,450.00 - $131,170.00 USD


Factors which may affect starting pay within this range may include geography/market, skills, education, experience, and other qualifications of the successful candidate.


If this is a commission eligible position the commission eligibility will be in accordance with the terms of the Company's plan. Commissions are based on individual performance and/or company performance.


The Company offers the following benefits for this position, subject to applicable eligibility requirements: medical insurance, dental insurance, vision insurance, 401(k) retirement plan. life insurance, long-term and short-term disability insurance, paid parking/public transportation, paid time off, paid sick and safe time.


Who we are

We are a team of more than 72,000 highly dedicated Healthineers in more than 70 countries. As a leader in medical technology, we constantly push the boundaries to create better outcomes and experiences for patients, no matter where they live or what health issues they are facing. Our portfolio is crucial for clinical decision-making and treatment pathways.


How we work

When you join Siemens Healthineers, you become one in a global team of scientists, clinicians, developers, researchers, professionals, and skilled specialists, who believe in each individual’s potential to contribute with diverse ideas. We are from different backgrounds, cultures, religions, political and/or sexual orientations, and work together, to fight the world’s most threatening diseases and enable access to care, united by one purpose: to pioneer breakthroughs in healthcare. For everyone. Everywhere. Sustainably.


To find out more about Siemens Healthineers businesses, please visit our company page here.


Equal Employment Opportunity Statement

Siemens Healthineers is an Equal Opportunity and Affirmative Action Employer encouraging diversity in the workplace. All qualified applicants will receive consideration for employment without regard to their race, color, creed, religion, national origin, citizenship status, ancestry, sex, age, physical or mental disability unrelated to ability, marital status, family responsibilities, pregnancy, genetic information, sexual orientation, gender expression, gender identity, transgender, sex stereotyping, order of protection status, protected veteran or military status, or an unfavorable discharge from military service, and other categories protected by federal, state or local law.


EEO is the Law: Applicants and employees are protected under Federal law from discrimination. To learn more, click here.


Reasonable Accommodations: Siemens Healthineers is committed to equal employment opportunity. As part of this commitment, we will ensure that persons with disabilities are provided reasonable accommodations.


If you require a reasonable accommodation in completing a job application, interviewing, completing any pre-employment testing, or otherwise participating in the employee selection process, please fill out the accommodations form here. If you’re unable to complete the form, you can reach out to our HR People Connect Peop le Contact Center for support at . Please note HR People Connect People Contact Center will not have visibility of your application or interview status.


California Privacy Notice: California residents have the right to receive additional notices about their personal information. To learn more, click here.


Export Control: “A successful candidate must be able to work with controlled technology in accordance with US export control law.” “It is Siemens Healthineers’ policy to comply fully and completely with all United States export control laws and regulations, including those implemented by the Department of Commerce through the Export Administration Regulations (EAR), by the Department of State through the International Traffic in Arms Regulations (ITAR), and by the Treasury Department through the Office of Foreign Assets Control (OFAC) sanctions regulations.”


Data Privacy: We care about your data privacy and take compliance with GDPR as well as other data protection legislation seriously. For this reason, we ask you not to send us your CV or resume by email. We ask instead that you create a profile in our talent community where you can upload your CV. Setting up a profile lets us know you are interested in career opportunities with us and makes it easy for us to send you an alert when relevant positions become open. Register here to get started.


Beware of Job Scams: Please beware of potentially fraudulent job postings or suspicious recruiting activity by persons that are currently posing as Siemens Healthineers recruiters/employees. These scammers may attempt to collect your confidential personal or financial information. If you are concerned that an offer of employment with Siemens Healthineers might be a scam or that the recruiter is not legitimate, please verify by searching for the posting on the Siemens Healthineers career site.


To all recruitment agencies: Siemens Healthineers does not accept agency resumes. Please do not forward resumes to our jobs alias, employees, or any other company location. Siemens Healthineers is not responsible for any fees related to unsolicited resumes.


#J-18808-Ljbffr

Related Jobs

View all jobs

Project Manager - Data Analytics (Supply Chain)

Project Manager – Data Governance & Regulatory Compliance (Microsoft Purview)

Senior Project Manager, Data Governance & Purview Compliance

GIS Data Engineer

Data Governance Manager

Manager/Senior Manager - Data Governance - BCBS 239 - Scaling Consultancy

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

How Many Data Science Tools Do You Need to Know to Get a Data Science Job?

If you’re trying to break into data science — or progress your career — it can feel like you are drowning in names: Python, R, TensorFlow, PyTorch, SQL, Spark, AWS, Scikit-learn, Jupyter, Tableau, Power BI…the list just keeps going. With every job advert listing a different combination of tools, many applicants fall into a trap: they try to learn everything. The result? Long tool lists that sound impressive — but little depth to back them up. Here’s the straight-talk version most hiring managers won’t explicitly tell you: 👉 You don’t need to know every data science tool to get hired. 👉 You need to know the right ones — deeply — and know how to use them to solve real problems. Tools matter, but only in service of outcomes. So how many data science tools do you actually need to know to get a job? For most job seekers, the answer is not “27” — it’s more like 8–12, thoughtfully chosen and well understood. This guide explains what employers really value, which tools are core, which are role-specific, and how to focus your toolbox so your CV and interviews shine.

What Hiring Managers Look for First in Data Science Job Applications (UK Guide)

If you’re applying for data science roles in the UK, it’s crucial to understand what hiring managers focus on before they dive into your full CV. In competitive markets, recruiters and hiring managers often make their first decisions in the first 10–20 seconds of scanning an application — and in data science, there are specific signals they look for first. Data science isn’t just about coding or statistics — it’s about producing insights, shipping models, collaborating with teams, and solving real business problems. This guide helps you understand exactly what hiring managers look for first in data science applications — and how to structure your CV, portfolio and cover letter so you leap to the top of the shortlist.

The Skills Gap in Data Science Jobs: What Universities Aren’t Teaching

Data science has become one of the most visible and sought-after careers in the UK technology market. From financial services and retail to healthcare, media, government and sport, organisations increasingly rely on data scientists to extract insight, guide decisions and build predictive models. Universities have responded quickly. Degrees in data science, analytics and artificial intelligence have expanded rapidly, and many computer science courses now include data-focused pathways. And yet, despite the volume of graduates entering the market, employers across the UK consistently report the same problem: Many data science candidates are not job-ready. Vacancies remain open. Hiring processes drag on. Candidates with impressive academic backgrounds fail interviews or struggle once hired. The issue is not intelligence or effort. It is a persistent skills gap between university education and real-world data science roles. This article explores that gap in depth: what universities teach well, what they often miss, why the gap exists, what employers actually want, and how jobseekers can bridge the divide to build successful careers in data science.