Job Description Responsible for developing, deploying, and monitoring Data Science solutions that involve Machine Learning, Deep Learning, GenAI, Agentic and other AI techniques.

Responsibilities Transform complex business challenges into scientific research problems Develop data-driven solutions to address business challenges using appropriate techniques (AI, ML, DL, GenAI etc.) Hands on data extraction, data analysis, data cleaning, preparation, modeling, and evaluation.

Conduct data analysis to support business cases, prove hypotheses, new ideas and proof of concepts.

Build and execute various data science projects for product and business use cases across the organization.

Deploy, document, maintain and monitor the developed solutions Presenting data science results to a variety of audience Protect the developed algorithms and solutions by patenting the technology and consider publishing at academic and industrial research conference.

Build prototypes and proof-of-concepts and conduct tool evaluations.

Lead projects independently end-to-end.

Knowledge dissemination by presenting work externally at conferences and Universities.





Collaborate with internal teams and across other Mastercard teams All about You At least 7 to 10 years of proven experience in developing and deploying Machine learning and Deep learning solutions end-to-end (data exploration to deployment).

Will consider even 5+ years if candidate has a Ph.D. from relevant areas.

Deep understanding of different Machine learning, Deep learning, GenAI and AI algorithms and the math behind it.

Strong scientific communication skills.

Handling data responsibly by maintaining data governance, privacy, and other standards Curious, Critical thinker, good hacking skills and scientific reasoning.

Not afraid to ask questions and propose current ideas Proactive in presenting contributions to diverse audiences and stakeholders.

Experience in building GenAI based solutions using LLM, SML, RAG, VectorDBs, and agentic frameworks.

Masters in computer science or quantitative field is a must, and PhD is good to have.

Skills Python, PySpark, SQL ML Frameworks, Deep Learning Frameworks, Agentic Frameworks Databricks, Hadoop, AWS/Azure.

📌 Data Scientist (Toronto)
🏢 ITMC Systems
📍 Toronto