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, positive hacking skills and scientific reasoning.
- Not afraid to ask questions and propose new 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