Applied Scientist, Demand Tech Planning
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Posting language
- English
- Posted
Original job description
Description
The Media Planning Science team develops and implements models that deliver insights and recommendations for strategic media planning and measurement across Amazon Advertising's product portfolio. Our mission is to help advertisers create and execute plans that meet their objectives while providing accurate measurement tools. We work on a multitude of problem statements that encompass Incremental Reach, Budget Planning Optimization, and Recommendations. Our models leverage both heuristic and machine learning approaches including deep learning techniques, with insights delivered through agent-based tools and APIs that integrate seamlessly into user interfaces and programmatic systems to ensure optimal advertising outcomes.
As an Applied Scientist on the team, you will be at the forefront of innovation, developing media planning solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel insights to our customers.
Key job responsibilities
You will solve real-world problems by analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop ML/DL models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal documents to share insights to audiences of varying levels of technical sophistication.
About The Team
We are a team of scientists across Applied and Data Science disciplines. You will work with colleagues with deep expertise in ML, DL, NLP, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.
Basic Qualifications
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, ON, Toronto - 149,300.00 - 249,300.00 CAD annually
The Media Planning Science team develops and implements models that deliver insights and recommendations for strategic media planning and measurement across Amazon Advertising's product portfolio. Our mission is to help advertisers create and execute plans that meet their objectives while providing accurate measurement tools. We work on a multitude of problem statements that encompass Incremental Reach, Budget Planning Optimization, and Recommendations. Our models leverage both heuristic and machine learning approaches including deep learning techniques, with insights delivered through agent-based tools and APIs that integrate seamlessly into user interfaces and programmatic systems to ensure optimal advertising outcomes.
As an Applied Scientist on the team, you will be at the forefront of innovation, developing media planning solutions end-to-end from inception to production. You will propose, design, analyze, and productionize models to provide novel insights to our customers.
Key job responsibilities
- Leverage deep expertise in one or more scientific disciplines to invent solutions to ambiguous ads measurement and media planning problems
- Disambiguate problems to propose clear evaluation frameworks and success criteria
- Work autonomously and write high quality technical documents
- Implement a significant portion of critical-path code, and partner with engineers to directly carry solutions into production
- Partner closely with other scientists to deliver large, multi-faceted technical projects
- Share and publish works with the broader scientific community through meetings and conferences
- Communicate clearly to both technical and non-technical audiences
- Contribute new ideas that shape the direction of the team's work
- Mentor junior scientists and participate in the hiring process
You will solve real-world problems by analyzing large amounts of data, generate business insights and opportunities, design simulations and experiments, and develop ML/DL models. The team is driven by business needs, which requires collaboration with other Scientists, Engineers, and Product Managers across the advertising organization. You will prepare written and verbal documents to share insights to audiences of varying levels of technical sophistication.
About The Team
We are a team of scientists across Applied and Data Science disciplines. You will work with colleagues with deep expertise in ML, DL, NLP, Gen AI, and Causal Inference with a diverse range of backgrounds. We partner closely with top-notch engineers, product managers, sales leaders, and other scientists with expertise in the ads industry and on building scalable modeling and software solutions.
Basic Qualifications
- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
- Currently has, or is in the process of obtaining, a PhD in computer science, computer engineering, or related field
- Experience applying theoretical models in an applied environment
- Experience applying generative AI techniques to solve complex scientific or business problems with measurable impact
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, ON, Toronto - 149,300.00 - 249,300.00 CAD annually
More about this job
Responsibilities
Develop, evaluate, and productionize machine learning and deep learning models that provide media planning and advertising measurement insights, including solutions for incremental reach, budget optimization, and recommendations. Collaborate with scientists, engineers, and product managers to deliver scalable solutions, communicate findings, publish scientific work, and mentor junior scientists.
Requirements
Requires at least three years of experience building models for business applications, plus a PhD or a master's degree with at least four years of experience in computer science, computer engineering, machine learning, or a related field. Candidates must have programming experience in Java, C++, Python, or a related language, and experience in areas such as algorithms, numerical optimization, data mining, or distributed computing; a PhD and applied generative AI experience are preferred.
Skills
- Applied Science
- Machine Learning
- Deep Learning
- Generative AI
- Causal Inference
- Media Planning
- Advertising Measurement
- Budget Optimization
- Incremental Reach
- Model Development
- Numerical Optimization
- Data Mining
- Algorithms and Data Structures
- Python
- Java
- C++
Benefits
- Health Insurance
- Dental Insurance
- Vision Insurance
- Prescription Coverage
- Basic Life and AD&D Insurance
- Deferred Profit Sharing Plan
- Paid Time Off
- Sign-On Payments
- Restricted Stock Units
Visa sponsorship
Not detected in the job text
Categories
- Science & Research
- Data & Analytics
- Technology
- Software
- Marketing
Keywords
- Amazon Advertising
- Media Planning
- Advertising Measurement
- Incremental Reach
- Budget Planning Optimization
- Recommendations
- Machine Learning
- Deep Learning
- Generative AI
- Natural Language Processing
- Causal Inference
- Heuristic Models
- Agent-Based Tools
- APIs
- Model Productionization
- Evaluation Frameworks
- Numerical Optimization
- Data Mining
- Algorithms and Data Structures
- Parallel Computing
- Distributed Computing
- High-Performance Computing
- Python
- Java
- C++
- Simulations
- Experiments
- Technical Documentation
- Scientific Research
- Toronto