Senior Data Science Consultant AWS Professional Services, AWS Professional Services
Role details
Job location
Tech stack
Job description
Senior Delivery Consultant - Machine Learning (GenAI), ProServe EMEA, AWS Professional Services, You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies. You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
In this role you will be capable of using GenAI and other techniques to design, evangelize, and implement and scale solutions for never-before-solved problems., * Lead end-to-end delivery of complex AI/ML engagements, from strategic planning through to pre-production deployment and optimization
- Architect and implement advanced solutions leveraging AWS's AI/ML services, with particular focus on Generative AI using Amazon Bedrock and SageMaker
- Provide technical leadership and mentorship to junior consultants while driving best practices across delivery teams
- Partner with customers to translate business challenges into measurable ML outcomes and clear delivery roadmaps
- Drive innovation in applied AI/ML, contributing to methodologies and reusable solutions across the practice
- Influence customer AI strategy through technical expertise and industry insights
- Lead multi-disciplinary teams and coordinate across stakeholder groups to deliver high-impact AI solutions
- Provide thought leadership in internal and external engagements
- Support pre-sales activities to provide technical expertise and review project scoping and risks
This role will be based in our AWS offices in Madrid, when not at the Customer site. About the team Diverse Experiences
Requirements
- Strong experience in building large scale machine learning or deep learning models and in Generative AI model development
- Experience in data and machine learning engineering and cloud native technologies
- Strong experience communicating across technical and non-technical audiences
- Strong experience facilitating discussions with senior leadership regarding technical / architectural trade-offs, best practices, and risk mitigation, * Master's degree in a quantitative field such as statistics, mathematics, data science, engineering, or computer science
- Knowledge of the primary AWS services (ec2, elb, rds, route53 & s3)
- Experience with software development life cycle (sdlc) and agile/iterative methodologies
- Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet
Benefits & conditions
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating - that's why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses. Inclusive Team Culture
Here at AWS, it's in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness. Mentorship & Career Growth
We're continuously raising our performance bar as we strive to become Earth's Best Employer. That's why you'll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional. Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there's nothing we can't achieve in the cloud.