Sr. Applied Scientist, Workforce Solutions

Description Success in any organization begins with its people and having a comprehensive understanding of our workforce and how we best utilize their unique skills and experience is paramount to our future success. WISE (Workforce Intelligence powered by Scientific Engineering) delivers the scientific and engineering foundation that powers Amazon's enterprise-wide workforce planning ecosystem. Addressing the critical need for precise workforce planning, WISE enables a closed-loop mechanism essential for ensuring Amazon has the right workforce composition, organizational structure, and geographical footprint to support long-term business needs with a sustainable cost structure. We are looking for a Sr. Applied Scientist to join our ML/AI team to work on Advanced Optimization and LLM solutions. You will partner with Software Engineers, Machine Learning Engineers, Data Engineers and other Scientists, TPMs, Product Managers and Senior Management to help create world-class solutions. We're looking for people who are passionate about innovating on behalf of customers, demonstrate a high degree of product ownership, and want to have fun while they make history. You will leverage your knowledge in machine learning, advanced analytics, metrics, reporting, and analytic tooling/languages to analyze and translate the data into meaningful insights. You will have end-to-end ownership of operational and technical aspects of the insights you are building for the business, and will play an integral role in strategic decision-making. Further, you will build solutions leveraging advanced analytics that enable stakeholders to manage the business and make effective decisions, partner with internal teams to identify process and system improvement opportunities. As a tech expert, you will be an advocate for compelling user experiences and will demonstrate the value of automation and data-driven planning tools in the People Experience and Technology space. Key job responsibilities Engineering execution - drive crisp and timely execution of milestones, consider and advise on key design and technology trade-offs with engineering teams Priority management - manage diverse requests and dependencies from teams Process improvements – define, implement and continuously improve delivery and operational efficiency Stakeholder management – interface with and influence your stakeholders, balancing business needs vs. technical constraints and driving clarity in ambiguous situations Operational Excellence – monitor metrics and program health, anticipate and clear blockers, manage escalations To be successful on this journey, you love having high standards for yourself and everyone you work with, and always look for opportunities to make our services better. Basic Qualifications 3+ years of building machine learning models for business application experience PhD, or Master's degree and 6+ years of applied research experience Experience programming in Java, C++, Python or related language Experience with neural deep learning methods and machine learning Preferred Qualifications Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. Experience with large scale distributed systems such as Hadoop, Spark etc. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. The base salary range for this position is listed below. As a total compensation company, Amazon's package may include other elements such as sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon offers comprehensive benefits including health insurance (medical, dental, vision, prescription, basic life & AD&D insurance), Registered Retirement Savings Plan (RRSP), Deferred Profit Sharing Plan (DPSP), paid time off, and other resources to improve health and well-being. We thank all applicants for their interest, however only those interviewed will be advised as to hiring status. CAN, BC, Vancouver - 195,900.00 - 327,200.00 CAD annually

The role involves developing advanced optimization and LLM solutions to power Amazon's workforce planning ecosystem. You will lead engineering execution, manage stakeholders, and translate data into strategic insights for workforce composition and organizational structure.

Requires a PhD or Master's degree with significant applied research experience and at least 3 years of building ML models for business. Proficiency in Python, Java, or C++ and experience with deep learning methods are essential.

• Health insurance • Medical insurance • Dental insurance • Vision insurance • Prescription insurance • Basic life & AD&D insurance • Registered Retirement Savings Plan (RRSP) • Deferred Profit Sharing Plan (DPSP) • Paid time off

• Apprentissage automatiqueSouhaitée
• PythonSouhaitée
• JavaSouhaitée
• C++Souhaitée

Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.

• Machine Learning
• Advanced Optimization
• Large Language Models
• Python
• Java
• C++
• Neural Deep Learning
• Advanced Analytics
• R
• Scikit-learn
• Spark MLLib
• MxNet
• Tensorflow
• Numpy
• Scipy
• Hadoop

• Science & Research
• Data & Analytics
• Technology
• Software
• Engineering

Formation minimale

Maîtrise

Expérience minimale

5+ ans

Postuler avant le

11 sept. 2026

Langue de l’offre

anglais

Heures de travail

40 heures par semaine

Niveau d’expérience

Mid-Senior level