Position Details- Role: Senior Data Scientist (Level 7)
- Location: Toronto, Canada
- Duration: Long-Term
- Hours: 40 Hours/Week
- Work Arrangement: Hybrid
Position Overview This team supports the company's cybersecurity products through advanced analytics and machine learning. The team's primary focus is connecting cybersecurity datasets with the core transaction data to identify fraud patterns, generate insights, and support product decision-making.
One example of the team's work is identifying compromised or "bridge" merchants by analyzing relationships between cybersecurity events and transaction activity.
Key RequirementsTechnical Skills- Strong Python and SQL proficiency with daily hands-on coding
- Experience processing large-scale datasets using PySpark
- Experience building and maintaining data pipelines
- Strong machine learning and statistical modeling background
- Experience with Python libraries such as Pandas, NumPy, and Scikit-learn
Domain Experience- Cybersecurity or fraud analytics experience is preferred but not required
- Experience working with large transactional or financial datasets is highly valued
- Ability to derive business insights from complex data sources
Project Focus- Support cybersecurity and fraud-related products
- Build machine learning and analytical solutions
- Connect cybersecurity data with transaction data to identify threats and patterns
- Analyze large datasets and deliver actionable recommendations
- Develop scalable analytics and data processing solutions
Team Structure- Direct team: 4 members based primarily in New York
- Broader Cyber Analytics team: Approximately 18 members across Toronto, New York, and Salt Lake City
- Toronto-based resources available to support onboarding and collaboration
Interview Process- Round 1: Technical Interview
- Round 2: Behavioral Interview
Recruiting Focus Prioritize candidates with:
- Strong Python, SQL, and PySpark experience
- Proven machine learning and statistical modeling expertise
- Experience handling large-scale datasets
- Background in fraud analytics, cybersecurity analytics, risk analytics, payments, or financial services
- Recent hands-on coding experience rather than primarily managerial responsibilities
