# Lead Data Scientist (Graph Analytics)

**Company**: Mastercard
**Location**: Toronto
**Experience**: senior
**Job type**: full-time
**Salary**: $127,000 - $203,000 CAD
**Category**: Data Science
**Industry**: Finance

**Apply**: https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Toronto-Canada/Lead-Data-Scientist_R-293166?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_7fba8d0f-6fd

## Description

Mastercard is seeking a highly skilled and motivated Lead Data Scientist to join its Cyber Analytics team within the Security Solutions Data Science organisation.

The successful candidate will play a leadership role in developing advanced analytics and machine learning solutions across cybersecurity, payments, and fraud. This person will also have formal people-management responsibilities for junior team members, helping them grow their technical capabilities, manage priorities, and deliver high-quality work.

**Job Responsibilities:**

- Lead the design, development, validation, and implementation of advanced analytical solutions, predictive models, and machine learning algorithms using large-scale payment, fraud, merchant, cybersecurity, and threat-intelligence data.

- Provide technical leadership for graph analytics and modeling, including graph schema design, relationship modeling, community detection, link analysis, graph embeddings, and graph neural networks.

- Develop models and analytical methods that identify complex or indirect risk patterns across interconnected entities.

- Apply graph algorithms and machine learning techniques to identify hidden communities, shared infrastructure, anomalous relationships, compromise paths, and patterns.

- Work hands-on with Python, SQL, Spark, Hadoop, and Databricks to develop scalable data-processing pipelines, reusable analytical datasets, model features, and production-ready solutions.

- Define performance metrics, validation strategies, monitoring requirements, and business-outcome measures for machine learning solutions.

- Translate ambiguous business, product, cybersecurity, and fraud problems into clearly defined analytical approaches, technical requirements, and delivery plans.

- Partner with product, data engineering, software engineering, cybersecurity, operations, and other data science teams to move analytical capabilities from research through production deployment.

- Communicate analytical findings, model performance, technical tradeoffs, risks, and business implications clearly to technical and non-technical stakeholders.

- Provide regular coaching, technical guidance, career-development support, and actionable feedback to junior team members.

**Requirements:**

- Bachelor’s or Master’s degree in Data Science, Computer Science, Cybersecurity, Information Technology, Engineering, Mathematics, Statistics, Physics, or a related quantitative field.

- Proven experience leading data science projects from problem definition and exploratory research through validation, implementation, and production handoff.

- Strong collaborator who can work across data science, product, engineering, cybersecurity, and operations teams.

- Organized, accountable, and comfortable managing multiple priorities in an environment where analytical requirements and technical architecture continue to evolve.

- Confident working independently while maintaining the humility to seek additional expertise, consider alternative approaches, and incorporate feedback.

**Technical Skills:**

- Substantial hands-on knowledge of graph analytics, including designing graph data models, engineering node and edge features, and developing graph-based machine learning solutions at scale.

- Advanced proficiency in Python and SQL.

- Substantial hands-on experience with Apache Spark, Hadoop, and Databricks.

- Strong knowledge of statistical modeling, supervised and unsupervised machine learning, anomaly detection, feature engineering, model evaluation, and model-performance monitoring.

**Benefits:**

- Competitive pay based on location, experience, and other qualifications for the role.

- May be eligible to participate in a discretionary annual incentive program.

## Skills

### Required
- Python
- SQL
- Apache Spark
- Hadoop
- Databricks
- graph analytics
- machine learning
- statistical modeling
- anomaly detection
- feature engineering

### Nice to have
- web application security
- common cyber vulnerabilities
- threat vectors
- attack techniques
- payment-card fraud

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Source: [Apply at mastercard.wd1.myworkdayjobs.com](https://mastercard.wd1.myworkdayjobs.com/en-US/CorporateCareers/job/Toronto-Canada/Lead-Data-Scientist_R-293166?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)