Lead Data Scientist (Graph Analytics)

Skillhub Solutions Inc.; Toronto; In loco; CAD 127.000 - 203.000; Tempo pieno

Vantaggi offerti da questo lavoro

Discretionary annual incentive program

Descrizione del lavoro

Mastercard in Toronto, ON is seeking a Lead Data Scientist for its Cyber Analytics team within Security Solutions Data Science. You will lead graph analytics, design scalable data pipelines, and develop ML solutions for payments, fraud, and cybersecurity while mentoring junior team members.

The role requires advanced Python/SQL, Spark/Hadoop/Databricks expertise and strong modeling skills. Collaboration with cross-functional teams and delivering business outcomes are essential.

Competenze

• Bachelor's or Master's degree in a quantitative field.
• Experience leading data science projects from problem definition through production handoff.
• Hands-on graph analytics experience including graph data modeling, node/edge features, and scalable ML.
• Advanced Python and SQL; extensive Spark, Hadoop, and Databricks experience.
• Strong knowledge of statistical modeling, ML, anomaly detection, feature engineering, evaluation, and monitoring.
• Cybersecurity, web app security, threat-vector, or payments fraud knowledge is helpful.

Mansioni

• Design, develop, validate, and implement analytical solutions and ML algorithms using large-scale payments, fraud, and security data.
• Lead graph analytics and modeling including schema design, community detection, link analysis, graph embeddings, and GNNs.
• Identify hidden communities, anomalous relationships, and risk patterns across connected entities.
• Build scalable data pipelines and production-ready solutions with Python, SQL, Spark, Hadoop, and Databricks.
• Define model performance metrics, validation, monitoring, and business outcomes.
• Collaborate with product, engineering, cybersecurity, operations, and data science teams; communicate findings to stakeholders.
• Coach and provide technical guidance to junior team members.

Conoscenze

Graph analytics

Python

SQL

Apache Spark

Hadoop

Databricks

Machine Learning

Model evaluation

Threat analytics

Formazione

Bachelor's or Master's degree in a quantitative or related field

Strumenti

Databricks

Spark

Hadoop

Descrizione del lavoro

Toronto, ON Full-time CA$127,000 - CA$203,000 / year

Lead Data Scientist (Graph Analytics)

Mastercard is seeking a Lead Data Scientist for its Cyber Analytics team within Security Solutions Data Science. The role develops analytics and machine-learning solutions for cybersecurity, payments, and fraud, and includes people-management responsibilities for junior team members.

Responsibilities

• Design, develop, validate, and implement analytical solutions, predictive models, and machine-learning algorithms using large-scale payments, fraud, merchant, cybersecurity, and threat-intelligence data.
• Lead graph analytics and modeling, including graph schema design, relationship modeling, community detection, link analysis, graph embeddings, and graph neural networks.
• Identify hidden communities, anomalous relationships, compromise paths, and risk patterns across connected entities.
• Use Python, SQL, Spark, Hadoop, and Databricks to build scalable data pipelines, analytical datasets, model features, and production-ready solutions.
• Define model performance metrics, validation strategies, monitoring requirements, and business-outcome measures.
• Partner with product, engineering, cybersecurity, operations, and data science teams to deploy analytical capabilities; communicate findings and tradeoffs to technical and non-technical stakeholders.
• Coach and provide technical guidance, career-development support and feedback to junior team members.

Qualifications

• Bachelor's or Master's degree in a quantitative or related field.
• Experience leading data science projects from problem definition and research through validation, implementation, and production handoff.
• Substantial hands-on graph analytics experience, including graph data modeling, node and edge feature engineering, and scalable graph-based machine learning.
• Advanced Python and SQL skills and substantial experience with Apache Spark, Hadoop, Databricks, and distributed datasets.
• Strong knowledge of statistical modeling, machine learning, anomaly detection, feature engineering, model evaluation, and performance monitoring.
• Cybersecurity, web application security, threat-vector, or payment-card fraud knowledge is helpful.

Compensation

Toronto pay range: $127,000-$203,000 CAD. The successful candidate may also be eligible for a discretionary annual incentive program.