Fraud & GeoML Data Scientist (Hybrid)

GeoComply; Canada; Hybrid; CAD 80,000 - 100,000; Full time

Job summary

A leading technology company in Canada seeks a data scientist to develop and deploy machine learning models for fraud detection and geolocation verification. The candidate should have a strong background in statistics, programming in Python, and experience with machine learning libraries. A bachelor's degree in a quantitative field is required, with preferred experience in predictive modeling. Join a collaborative team that embraces innovation and diversity, contributing to key projects in a hybrid work environment.

Benefits

Hybrid working mode

Professional development budget

20 annual leave days

Premium health insurance

Competitive salary package

Attractive bonuses

Annual company trip

Quarterly team-building activities

In-office snacks and drinks

Qualifications

• 3-5 years of experience in data science or machine learning.
• Strong experience deploying models in production.
• Ability to work independently on complex problems.

Responsibilities

• Design and deploy machine learning models for fraud detection.
• Analyze complex fraud patterns to improve detection.
• Collaborate with cross-functional teams on ML projects.

Skills

Python programming

Machine learning libraries (Scikit-learn, XGBoost)

Data analysis

SQL querying

Model evaluation metrics

Statistics and probability

Data visualization tools (Matplotlib, Seaborn)

Education

Bachelor's or Master's degree in Computer Science, Statistics, or related field

Tools

Databricks

Spark

Git

Job description

A leading technology company in Canada seeks a data scientist to develop and deploy machine learning models for fraud detection and geolocation verification. The candidate should have a strong background in statistics, programming in Python, and experience with machine learning libraries. A bachelor's degree in a quantitative field is required, with preferred experience in predictive modeling. Join a collaborative team that embraces innovation and diversity, contributing to key projects in a hybrid work environment.