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For Companies At a Glance
- Tasks: Design scalable, data-driven solutions for dynamic retail organisations using AI and machine learning.
- Company: Join NVIDIA, a leading tech company known for innovation and collaboration.
- Benefits: Competitive salary, health benefits, remote work options, and opportunities for professional growth.
- Why this job: Make a real impact in retail by deploying cutting-edge AI solutions and optimising operations.
- Qualifications: MS or PhD in a technical field with 5+ years of relevant experience.
- Other info: Be part of a creative team driving technology adoption in the retail sector.
The predicted salary is between 36000 - 60000 £ per year.
Are you passionate about designing scalable, data-driven solutions for some of the world’s most dynamic retail organizations? We’re looking for a Solution Architect to join NVIDIA’s EMEA Retail Team, focusing on supply chain data science: forecasting, business analytics, and operations optimization. In this role, you’ll help leading Retail and CPG companies AI platforms that bring predictive intelligence and automation to every layer—from real-time demand planning and logistics optimization to customer recommendation tools. You’ll combine your deep knowledge of data systems, analytics frameworks, and machine learning pipelines with NVIDIA’s industry-leading GPU and AI platforms to drive measurable business impact across global retail ecosystems.
What You’ll Be Doing:
- You will be part of our EMEA Retail Solution Architecture Team working to drive NVIDIA technology adoption at key Retail & CPG customers and secure design wins in both Data Center, Edge and Cloud Deployments.
- Becoming a trusted technical advisor with our customers, work on exciting projects and deploy AI solutions in production using Data Processing for Retail.
- Leading customer proof-of-concepts (PoCs) of next-gen platforms for deploying Retail Industry solutions to key use-cases like forecasting, logistics, and customer recommendation and personalization, real-time and at scale.
- Collaborating with NVIDIA Engineering, Product, Sales teams on innovative AI optimization techniques, operating at the intersection of algorithms and systems, for assistance in developing solutions and providing customer feedback to enable development and growth of our products.
- Driving adoption of NVIDIA's Accelerated Compute Platforms with focus on growing our customer's Software, DevOps and MLOps capabilities by using NVIDIA's modern architectures, solutions and blueprints to deploy leading computing platforms.
What We Need to See:
- MS or PhD in Computer Science, Engineering, Mathematics, or related technical field (or equivalent experience).
- 5+ years of experience in data architecture, data science solutions, or large-scale analytics systems, working with enterprise developers and academic research community.
- Demonstrate detailed industry knowledge of Retail Analytics (demand forecasting, supply chain optimization, personalized recommendations, …)
- Experience with ML frameworks or data science stacks (PyTorch, TensorFlow, RAPIDS, etc.) and deep understanding of data pipelines, ETL processing, and real-time data streaming, parallel or distributed frameworks (e.g., Spark, Kafka, Databricks, Snowflake).
- Enjoy collaborating with teams across the organization such as Engineering/Research, Sales, Product, and Marketing, able to think creatively to debug and solve complex problems.
- Excellent communication and presentation skills with the ability to drive technical discussions with both engineers and executives.
Ways to Stand Out from the Crowd:
- Expertise in supply chain optimization, recommender systems, or behavioral data analytics at large scale.
- Strong fundamentals in optimization and decision intelligence (e.g., linear/ mixed-integer programming, routing, allocation, or planning algorithms).
- Experience with NVIDIA GPUs and software libraries, such as CuOpt, cuVS, RAPIDS, NeMo Retriever or NVIDIA NeMo Framework.
- Prior experience with AI at scale on cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure.
- Experience with containerization and orchestration technologies, monitoring, and observability solutions for AI deployments.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you.
Solution Architect, Data Science - Retail in Folkestone employer: Nvidia
Contact Detail:
Nvidia Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Solution Architect, Data Science - Retail in Folkestone
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the retail and data science space. Attend industry events, webinars, or even local meetups. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to data architecture and analytics. This is your chance to demonstrate your expertise in ML frameworks and real-time data processing. Make it easy for potential employers to see what you can do!
✨Tip Number 3
Don’t just apply—engage! When you find a role that excites you, reach out to current employees on LinkedIn. Ask them about their experiences and share your enthusiasm for the position. This personal touch can make a big difference in getting noticed.
✨Tip Number 4
Keep it fresh! Stay updated on the latest trends in AI and retail analytics. Follow relevant blogs, podcasts, and thought leaders. This knowledge will not only help you in interviews but also show that you're genuinely passionate about the field. And remember, apply through our website for the best chance!
We think you need these skills to ace Solution Architect, Data Science - Retail in Folkestone
Some tips for your application 🫡
Tailor Your CV: Make sure your CV speaks directly to the role of Solution Architect in Data Science. Highlight your experience with data architecture and analytics systems, especially in retail. We want to see how your skills align with what we’re looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Share your passion for designing scalable solutions and how your background fits into our mission at NVIDIA. Let us know why you’re excited about working with retail organisations and AI platforms.
Showcase Relevant Projects: If you've worked on projects related to forecasting, logistics, or customer recommendations, make sure to include them! We love seeing real-world applications of your skills, so don’t hold back on the details.
Apply Through Our Website: We encourage you to apply through our website for the best chance of getting noticed. It’s the easiest way for us to keep track of your application and ensure it reaches the right people. We can’t wait to see what you bring to the table!
How to prepare for a job interview at Nvidia
✨Know Your Data Inside Out
Make sure you have a solid grasp of data architecture and analytics frameworks. Brush up on your knowledge of supply chain optimisation and personalised recommendations, as these are key areas for the role. Be ready to discuss specific projects where you've applied these concepts.
✨Showcase Your Technical Skills
Prepare to talk about your experience with ML frameworks like PyTorch or TensorFlow, and be ready to dive into details about data pipelines and ETL processes. Highlight any hands-on experience you have with NVIDIA GPUs or cloud environments, as this will set you apart from other candidates.
✨Communicate Clearly and Confidently
Practice explaining complex technical concepts in simple terms. You’ll need to engage with both engineers and executives, so being able to adapt your communication style is crucial. Consider doing mock interviews to refine your presentation skills.
✨Demonstrate Your Problem-Solving Skills
Be prepared to tackle hypothetical scenarios related to retail analytics during the interview. Think creatively about how you would approach debugging or optimising a system. Show them your thought process and how you can drive innovative solutions.
