Sr. Applied Scientist, Workforce Solutions – Amazon – Vancouver, BC
Location: Vancouver, BC | Company: Amazon
Amazon’s WISE (Workforce Intelligence powered by Scientific Engineering) team is hiring a Senior Applied Scientist to join their ML/AI group in Vancouver, BC. If you’re passionate about building advanced optimization and LLM solutions that shape enterprise-wide workforce planning, this is a role where your work will directly influence how one of the world’s largest companies manages its people and operations at scale.
This position sits at the intersection of machine learning, advanced analytics, and strategic decision-making. You’ll collaborate closely with Software Engineers, ML Engineers, Data Engineers, TPMs, and Senior Management to develop world-class tools in the People Experience and Technology space — with full end-to-end ownership of the solutions you build.
About the Role: Sr. Applied Scientist, Workforce Solutions
The WISE platform powers Amazon’s enterprise workforce planning ecosystem, ensuring the company has the right organizational structure, workforce composition, and geographic footprint to meet long-term business goals sustainably. As a Senior Applied Scientist, you’ll be responsible for both the operational and technical aspects of the analytical insights you build — from design through deployment. You’ll translate complex data into meaningful outcomes, advocate for compelling user experiences, and champion automation and data-driven planning tools across the organization.
Beyond technical execution, this role demands strong stakeholder management and the ability to drive clarity in ambiguous situations. You’ll balance competing priorities, monitor program health, and continuously improve delivery processes — all while maintaining a high standard of operational excellence. Collaboration and influence are just as important here as deep technical expertise.
Benefits and Salary
The base salary range for this position in Vancouver, BC is $195,900 to $327,200 CAD annually. As a total compensation company, Amazon’s package may also include sign-on payments and restricted stock units (RSUs), with final compensation based on experience, qualifications, and location. Amazon offers a comprehensive benefits package that includes health insurance (medical, dental, vision, prescription, and basic life & AD&D), a Registered Retirement Savings Plan (RRSP), a Deferred Profit Sharing Plan (DPSP), paid time off, and additional resources to support health and well-being.
Job Details
🏢 Company: Amazon Development Centre Canada ULC
📍 Location: Vancouver, BC
🆔 Job ID: 10499244
💰 Pay: $195,900 – $327,200 CAD annually
Responsibilities
In this role, you’ll be driving the full lifecycle of ML and AI solution development — from scoping and design through to deployment and continuous improvement. Your day-to-day work will blend technical leadership with cross-functional collaboration, requiring you to balance innovation with operational rigour across a complex, high-stakes workforce planning environment.
- Drive engineering execution by managing crisp, timely delivery of milestones and advising on key design and technology trade-offs with engineering teams
- Manage priorities across diverse requests and dependencies from multiple teams simultaneously
- Define and implement process improvements to continuously enhance delivery and operational efficiency
- Engage stakeholders at all levels, balancing business needs against technical constraints and driving clarity in ambiguous situations
- Maintain operational excellence by monitoring metrics and program health, anticipating blockers, and managing escalations proactively
- Build advanced analytics solutions that enable stakeholders to manage the business and make effective, data-informed decisions
- Leverage machine learning and deep learning methods to develop optimization and LLM solutions that power workforce planning at scale
Requirements / Skills
The ideal candidate brings a strong academic and applied background in machine learning combined with hands-on experience shipping production-grade models. Amazon values scientists who take end-to-end ownership, thrive in ambiguous environments, and can influence both technical and non-technical stakeholders with confidence.
- 3+ years of experience building machine learning models for business applications
- PhD, or Master’s degree with 6+ years of applied research experience
- Programming proficiency in Java, C++, Python, or a related language
- Experience with neural deep learning methods and machine learning frameworks
- Familiarity with modelling tools such as R, scikit-learn, Spark MLLib, MXNet, TensorFlow, NumPy, or SciPy (preferred)
- Experience with large-scale distributed systems such as Hadoop or Spark is a strong asset
How to Apply
To apply, visit the official Amazon job posting using the link below. Make sure your resume is up to date and tailored to highlight your ML/AI research and engineering experience before submitting.
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Job Summary & Tips for Applying
Quick Summary & What to Highlight: This Sr. Applied Scientist role at Amazon in Vancouver is perfect for candidates who excel in machine learning model development, advanced optimization techniques, and stakeholder communication. On your resume, emphasize any experience with LLMs, deep learning frameworks, or large-scale distributed systems, your ability to drive end-to-end ML solutions, and your comfort working in a fast-paced, ambiguous environment. If you’ve previously worked in workforce analytics, people technology, or enterprise AI platforms, make sure to highlight specific achievements and responsibilities that align with this position.
Resume & Application Tips: Before applying, tailor your resume to match the job description. Include keywords like applied scientist, workforce planning, and machine learning optimization that appear in the posting. Quantify your achievements where possible (e.g., “reduced model inference latency by 30%” or “deployed ML pipeline serving 10M+ workforce records”). Write a brief cover letter expressing your genuine interest in Amazon‘s WISE team and why you’re excited about this opportunity in Vancouver. Double-check your application for spelling errors and ensure your contact information is current.
Interview Preparation: If selected for an interview, research Amazon‘s Leadership Principles, recent AI/ML initiatives, and the WISE platform’s role within the broader People Experience and Technology organization. Prepare specific examples using the STAR method (Situation, Task, Action, Result) to demonstrate your ML engineering, research, and cross-functional collaboration skills. Common questions may include scenarios about handling ambiguous problem definitions, prioritizing across competing stakeholder requests, and building scalable ML solutions. Dress appropriately for a technology environment, arrive 10–15 minutes early (or log in early for virtual interviews), and bring copies of your resume. Prepare thoughtful questions about the WISE team’s roadmap, engineering culture, and growth opportunities. After the interview, send a thank-you email within 24 hours reiterating your interest in the position.
