Senior Applied Scientist, Amazon

DESCRIPTION

We're looking for an entrepreneurial and resourceful individual to join the Advertiser Content Intelligence and Activation team as part of the Amazon Advertising Business.

The team is a core product team supporting all Amazon Ads businesses and providing innovative and scalable solutions to Advertisers and Advertising content creators problems.

Advertisers know that the quality and quantity of ad experience they are building are an increasingly large contributor to campaign performance.

However, the science behind "what makes an effective ad experience" is at best nascent and advertisers lack the resources and technology to activate and optimize their advertising content at scale.

This represents an important opportunity for Amazon to Innovate on behalf of their customers. By expanding the type of content advertisers can use (e.

g AI Generated content, dynamic content) and by building a set of shared content activation and intelligence services, the team is responsible for turning advertiser content into a key driver of campaign performances and scale across all its ads products.

We host hundreds of millions of assets.

We build on top of large models, generate and serve multi-modal embeddings for text, images, and videos. Asset metadata and intelligence serves the needs of other Amazon Ads product teams (e.

g. improve the performance of Amazon Ads' content recommendation models, Bid Optimization models, Content Optimization Models, power creative performance insights, seed data for Generative AI models, automate content moderation and spec checking).

Key job responsibilities

• Perform hands-on analysis and modeling of enormous data sets to develop insights for Amazon advertising business,
• Meet with stakeholders, business and tech leaders at Amazon to communicate your next big initiative,
• Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale, and complexity,
• Run A / B experiments, gather data, and perform statistical analysis,
• Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving,
• Research and explore state-of-the-art and innovative machine learning approaches,
• Recruit Scientists to the team and provide mentorship.

We are open to hiring candidates to work out of one of the following locations :

Toronto, ON, CAN

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
• Knowledge of programming languages such as C / C++, Python, Java or Perl
• Experience programming in Java, C++, Python or related language
• Experience with neural deep learning methods and machine learning
• Statistics, Applied Mathematics, Operation Research, Economics or a related quantitative bachelor or master degree.
• At least 5 years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), or statistical / mathematical software (e.g. R, Weka, SAS, Matlab)
• 4+ years of data scientist experience
• Experience articulating business questions and using quantitative techniques to arrive at a solution using available data
• Experience in machine-learning methodologies (e.g., supervised and unsupervised learning, deep learning, etc.)
• Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical / mathematical software (e.g. R, SAS, or Matlab)
• Experience using one or more programming languages (e.g., Python, Java, C++, C, etc.).
• Experience with big data : processing, filtering, and presenting large quantities (100K to Millions of rows) of data.

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 degree in math, statistics, computer science, or related science field.
• Depth and breadth in quantitative knowledge. Excellent quantitative modeling, statistical analysis skills and problem-solving skills.

Sophisticated user of statistical tools.

• Experience processing, filtering, and presenting large quantities (Millions to Billions of rows) of data
• Combination of deep technical skills and business savvy enough to interface with all levels and disciplines within our customer's organization
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
• Excellent verbal and written communication skills with the ability to effectively advocate technical solutions to research scientists, engineering teams and business audiences
• Ability to develop experimental and analytic plans for data modeling processes, use of strong baselines, ability to accurately determine cause and effect relations
• Demonstrable track record of dealing well with ambiguity, prioritizing needs, and delivering results in a dynamic environment
• Experience in advertising, recommendation systems, computer vision, and generative AI is a plus

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected status.

If you would like to request an accommodation, please notify your Recruiter.