Research Scientist jobs in Canada

DESCRIPTION

The Amazon ORC Analytics team is looking for a creative problem solver, analytical and technically skilled Business Intelligence Engineer to join our dynamic team.

This role requires an individual with excellent statistical and analytical abilities, deep knowledge of business intelligence solutions and data engineering practices as well as proficiency in hypothesis testing, including parametric and non-parametric tests and is familiar with A/B testing, understanding factors like random assignment, statistical power, p-values, confidence intervals, potential biases along with strong grasp of frequentist statistics.

The ideal candidate will help us to build data pipelines and robust metrics decks, perform advanced statistical analysis, and measure the success of our model deployments. If you have a knack for translating complex data insights into actionable strategies and can communicate these effectively to both technical and non-technical audiences, we'd love to hear from you!

1. Collaborate with cross-functional teams to understand business needs and provide data-driven recommendations.
2. Ability to clearly articulate assumptions, methodologies, results, and implications.
3. Able to present deep dives and analysis to both technical and non-technical stakeholders, ensuring clarity and understanding.
4. Design and implement metrics to measure the success and effectiveness of classification models by understanding the nuances and potential pitfalls.
5. Use visualization tools and develop data pipelines to publish the metrics to internal and external stakeholders.
6. Implement various sampling techniques with the ability to handle issues arising from sampling, like sampling biases.
7. Complete statistical tests like hypothesis testing, including parametric and non-parametric tests and is familiar with A/B testing.

1. Experience with machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance.
2. Experience applying theoretical models in an applied environment.
3. Experience working as a Data Scientist.
4. Experience with data scripting languages (e.g. SQL, Python, R etc.) or statistical/mathematical software (e.g. R, SAS, or Matlab).

1. Experience in Python, Perl, or another scripting language.
2. Experience in a ML or data scientist role with a large technology company.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting decisions based on your experience and skills. We value your passion to discover, invent, simplify and build. Protecting your privacy and the security of your data is a longstanding top priority for Amazon.

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, protected veteran status, disability, age, or other legally protected status.