Lead Data Scientist

Princeton IT Services, Inc; Toronto; On-site; CAD 130,000 - 170,000; Full time

Job summary

Princeton IT Services, Inc. in Toronto is seeking a Lead Data Scientist to develop, deploy, and monitor data science solutions involving ML, DL, GenAI, and agentic approaches.

You will transform complex business challenges into research problems and lead projects end-to-end on site at 121 Bloor St E. The role requires 7–10 years in ML/DL end-to-end (5+ years with a PhD) and strong math, communication, and governance skills.

Qualifications

• 7–10 years experience in ML/DL end-to-end; 5+ years if PhD in relevant areas.
• Deep understanding of ML/DL/GenAI algorithms and the math behind them.
• Strong scientific communication skills.
• Handling data governance, privacy, and other standards.
• GenAI-based solutions using LLM, SML, RAG, VectorDBs, and agentic frameworks.
• Master's in computer science or quantitative field is a must, PhD is good to have.

Responsibilities

• Transform complex business challenges into scientific research problems.
• Develop data-driven solutions to address business challenges using AI/ML/DL/GenAI.
• Hands-on data extraction, data analysis, data cleaning, preparation, modeling, and evaluation.
• Conduct data analysis to support business cases, prove hypotheses, new ideas and PoCs.
• Build and execute data science projects for product and business use cases across the organization.
• Deploy, document, maintain and monitor the developed solutions.
• Present data science results to a variety of audiences.
• 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.

Skills

Python

PySpark

SQL

ML Frameworks

Deep Learning Frameworks

Agentic Frameworks

Education

Master's in computer science or quantitative field

Tools

Databricks

Hadoop

AWS

Azure

Job description

Lead Data Scientist

Location: 121 Bloor St E, Toronto, Canada (5 days onsite)

Summary

Our Purpose - We work to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. Our decency quotient, or DQ, drives our culture and everything we do inside and outside of our company. We cultivate a culture of inclusion for all employees that respects their individual strengths, views, and experiences. We believe that our differences enable us to be a better team, one that makes better decisions, drives innovation and delivers better business results.

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.
• Present data science results to a variety of audiences.
• Protect the developed algorithms and solutions by patenting the technology and consider publishing at academic and industrial research conferences.
• 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.

Qualifications

• At least 7 to 10 years of proven experience in developing and deploying machine learning and deep learning solutions end-to-end; 5+ years considered 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 them.
• 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 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.
• Master's 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.