Senior Applied Scientist, Measurement, Ad Tech, and Data Science (MADS)

Amazon is hiring a Senior Applied Scientist, Measurement, Ad Tech, and Data Science (MADS) in Toronto, Canada. It pays CAD 196k-CAD 327k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this applied scientist role is Builds AI ●●●●: the job is building AI systems.
The posting mentions TensorFlow, scikit-learn and Deep learning among its tools and skills.
Level classes it as a senior role.
Amazon has 20,000+ other open roles on Level.

AI in this role

Design, develop, and productionize advanced machine learning models and generative AI solutions for media planning and ad tech measurement.

TensorFlowscikit-learnDeep learningAPIsGenerative AIComputer visionNatural Language Processing

computer-visionnlpmachine-learningdata-sciencecausal-inferencepredictive-modelingad-tech

The Measurement, Ad Tech, and Data Science (MADS) team at Amazon Ads is at the forefront of developing innovative solutions that help tens of millions of advertisers understand the value of their ad spend while prioritizing customer privacy and measurement quality.

The Media Planning Science team, part of broader MADS 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 Reach and Frequency, 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 a Senior 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 set the technical vision and innovate on behalf of our customers. You will propose, design, analyze, and productionize models to provide novel measurement insights to our customers. You will partner with engineering to deploy these solutions into production. You will work with key stakeholders from various business teams to enable advertisers to act upon those metrics.

Key job responsibilities
* Lead the development of media planning models and solutions that address the full spectrum of an advertiser's investment, focusing on scalable and efficient methodologies.
* Collaborate closely with cross-functional teams including engineering, product management, and business teams to define and implement measurement solutions.
* Use state-of-the-art scientific technologies including Generative AI, Classical Machine Learning, Causal Inference, Natural Language Processing, and Computer Vision to develop state of the art models that measure the impact of media plans across different metrics.
* Drive experimentation and the continuous improvement of ML models through iterative development, testing, and optimization.
* Translate complex scientific challenges into clear and impactful solutions for business stakeholders.
* Mentor and guide junior scientists, fostering a collaborative and high-performing team culture.
* Foster collaborations between scientists to move faster, with broader impact.
* Regularly engage with the broader scientific community with presentations, publications, and patents.

A day in the life
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, Research, 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 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.
- PhD in engineering, technology, computer science, machine learning, robotics, operations research, statistics, mathematics or equivalent quantitative field

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, ON, Toronto - 195,900.00 - 327,200.00 CAD annually

How we rate this

Senior Applied Scientist, Measurement, Ad Tech, and Data Science (MADS) at Amazon rates 90 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

Senior Applied Scientist, Measurement, Ad Tech, and Data Science (MADS) is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is CAD 196k-CAD 327k a year.
The role is based in CA, ON, Toronto.
The job was posted on April 22, 2026.
Seniority: senior.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionNLPMachine learningData ScienceCausal InferencePredictive ModelingAd TechTensorFlow

Also common in applied scientist jobs at this level

LLM Reinforcement learning AWS PyTorch Fine-tuning SQL

Pay

Typical applied scientist job: $169k

Use the typical applied scientist figure as a reference when pay comes up. See applied scientist jobs

Questions you could be asked

Walk me through a computer vision problem you solved, from raw data to a deployed model.
What NLP problem have you worked on, and how did you measure whether it actually worked?
Tell me about a project where machine learning was part of your work. What did you do?
Tell me about a project where data science was part of your work. What did you do?
Tell me about a project where causal inference was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: Computer vision, NLP, Machine learning, Data Science, and Causal Inference. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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