Associate Data Scientist - User Fraud

Job description

We’re looking for a Data Scientist to join the band. You’ll help us expand detection and mitigation methods against abuse across all audio verticals on our platform. The team’s goal is to ensure a fraud-free experience for users and creators by employing advanced technology and evolving strategies to maintain fair engagement and accuracy.

As part of the team, you’ll contribute to our data-driven approach, protecting the platform's integrity from issues like account abuse and artificial manipulation. Your work will directly impact how billions of fans connect with millions of artists and creators, and how the world experiences content.

You’ll work with a team of data scientists and machine learning engineers to detect and prevent abuse on our platform. You’ll help us investigate anomalous trends, discover new ways to leverage data for improved detection methods, and identify unwanted behavior on the platform. We are a fast-paced team passionate about high-impact projects, and we prioritize continuous learning and skill development. You will have the freedom to refine your skills and working methods.

What You'll Do

Investigate evolving fraud trends and consumption habits to enhance detection capabilities.

Apply your expertise in quantitative analysis, data mining, and data presentation to help automate, optimize and understand key business problems and solutions.

Build data and tooling to empower operational and exploratory data analysis while optimizing for speed, accuracy, and quality.

Work closely with cross-functional teams of data and backend engineers, and product managers.

Partner with a broad range of stakeholders across music, podcasts and audiobooks to consistently uphold platform integrity.

Who You Are

A Bachelor's degree in Data Science, CS, or another quantitative field.

1+ years work experience with an emphasis on investigative data analysis, anomaly detection, and data pipelines.

Deep understanding of data with expertise in data manipulation and design (SQL) and experience in Python.

Strong analytical skills, with the ability to turn data into actionable insights and recommendations.

Strong problem-solving skills, intellectual curiosity, and a proactive approach to identifying new opportunities for fraud detection.

A continuous learner, excited by new technologies and able to pick up new tools and frameworks quickly.

Where You'll Be

This role is based in Toronto.
 
We offer you the flexibility to work where you work best! There will be some in person meetings, but still allows for flexibility to work from home.