Senior Data Scientist (Remote)

The Athletic; Canada; Remote; CAD 90,000 - 120,000; Full time

Job summary

A leading sports media company in Canada is seeking a senior data scientist to enhance their product using machine learning and data analysis. You will work closely with various teams to create models that drive engagement and optimize workflows. The ideal candidate has 4-6 years of experience in data science with strong skills in R or Python and SQL. This position offers a unique opportunity to make a significant impact in the sports journalism space.

Qualifications

• 4-6 years of experience as a data scientist solving real-world problems.
• Strong working knowledge of R or Python for machine learning.
• Broad understanding of SQL to handle data warehouses.
• Understand subscription media and recommendation engines.
• Ability to drive projects and prioritize high-impact work.
• Strong verbal and written communication skills.

Responsibilities

• Design, build, and implement mathematical models for product goals.
• Lead projects with hands-on analysis from multiple analytical methods.
• Use quantitative analysis to understand user feedback and develop recommendations.
• Design and develop data science pipelines in production.
• Guide complex experiments and foster a great data science environment.

Skills

Data analysis

Machine learning

SQL

R or Python

Statistical principles

Communication skills

Job description

About Us

Powered by one of the largest global newsrooms in sports media, The Athletic brings sports fans the most comprehensive stories about the teams, sports and athletes they love. The Athletic’s newsroom of 450+ full-time staff delivers in-depth coverage of hundreds of professional and college teams across more than 47 North American markets and all 20 football clubs in the English Premier League, as well as many Championship clubs.

About the Role

We are looking for a senior data scientist who will bring a deep understanding of our sportswriting, our in-game experience, and the way our subscribers use The Athletic to help us make our best-in-class product even better. In this role, you will work closely with our data, product, growth, and engineering teams to develop advanced machine learning models. These models will help us understand our business, optimize and automate our workflows, and have our product make smarter recommendations. As a member of our small data science team, your work will have a significant impact at The Athletic.

Responsibilities

• Design, build, and implement mathematical models to drive key long-term product goals, like training a model that predicts which of our free users are most likely to subscribe, or recommending the right articles to the right users at the right time.
• Lead projects with hands-on analysis and modeling, drawing from multiple analytical methods to choose the right tool and right level of complexity appropriate for the job.
• Use quantitative analysis to deeply understand what our users are saying, and to develop recommendations based on that analysis.
• Design and develop data science pipelines in production.
• Guide complex experiments.
• Cultivate an outstanding data science environment.

Requirements

• 4-6 years of experience as a data scientist with a proven ability to apply scientific methods to solve real-world problems on web scale data.
• Strong working knowledge of a scripting language like R or Python and how to use it to train machine learning models and put them into production.
• A broad understanding of SQL with an ability to efficiently pull and write to our data warehouses.
• An understanding of subscription media and recommendation engines, with the ability to turn it into insights and optimizations.
• Knowledge of statistical principles and how they apply to predictive modeling.
• Ability to drive projects with minimal guidance and prioritize high-impact work.
• Strong verbal and written communication skills with ability to build cross-functional relationships.
• Can explain sophisticated concepts to diverse audiences and craft compelling stories with data.