Data Science Lead

Data Science Lead

Date: Jan 27, 2026

Location: Toronto, ON, CA, M5C 3G7

Company: Deloitte

Job Type: Permanent

Work Model: Hybrid

Reference code: 131930

Primary Location: Toronto, ON

All Available Locations: Toronto, ON; Burlington, ON; Kitchener, ON

Our Purpose

At Deloitte, our Purpose is to make an impact that matters. We exist to inspire and help our people, organizations, communities, and countries to thrive by building a better future. Our work underpins a prosperous society where people can find meaning and opportunity. It builds consumer and business confidence, empowers organizations to find imaginative ways of deploying capital, enables fair, trusted, and functioning social and economic institutions, and allows our friends, families, and communities to enjoy the quality of life that comes with a sustainable future. And as the largest 100% Canadian-owned and operated professional services firm in our country, we are proud to work alongside our clients to make a positive impact for all Canadians.

By living our Purpose, we will make an impact that matters.

• Have many careers in one Firm.
• Enjoy flexible, proactive, and practical benefits that foster a culture of well-being and connectedness.
• Learn from deep subject matter experts through mentoring and on the job coaching

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What will your typical day look like?

• Lead, manage, and mentor a team of data scientists, machine learning engineers, and big data specialists to deliver innovative and scalable data-driven solutions.
• Plan, prioritize, and oversee data science projects that align with organizational goals, collaborating with cross-functional teams to define and meet business requirements.
• Design, build, and deploy analytical systems, predictive models, and machine learning algorithms that leverage large volumes of structured and unstructured data.
• Ensure data quality, integrity, and veracity through rigorous data mining, cleaning, and validation processes.
• Interpret complex data problems, analyze results, and communicate actionable insights and recommendations to both technical teams and business stakeholders.
• Champion best practices in model development, testing, and operationalization, including monitoring and improving model performance post-deployment.
• Drive innovation by experimenting with new models, techniques, and technologies, and stay current with advancements in data science and AI.
• Develop and implement strategies for data collection and integration from diverse sources, ensuring scalability and reliability of data pipelines.
• Facilitate knowledge sharing, collaboration, and continuous learning within the data science team and across the wider organization.
• Lead the creation of data visualizations, reports, and presentations to articulate findings and influence business decisions.

About the team

Delo is building the next generation of enterprise AI: digital teammates that automate the work humans shouldn’t do, starting with Finance and expanding across the back office. Born inside Deloitte and now backed by the firm, Delo is creating Deloitte 2.0: a fully digital, AI-native version of the firm. Our platform orchestrates agentic AI, structured SOPs, and automated workflows across ERPs, CRMs, tax engines, and financial systems. Think: a reusable, multi-agent operating system for enterprise work. We’re early, truly 0→1, and building a scalable engineering foundation that will power dozens of agents, thousands of teams, and millions of automated tasks. If you want to build foundational infrastructure that will power AI-driven work for thousands of organizations, this is the moment to join.

Enough about us, let’s talk about you

• Experience with deploying and operationalizing machine learning models in production environments.
• Experienced data science leader with a proven track record managing and growing high-performing data science teams.
• Skilled in advanced statistical modeling, machine learning, natural language processing, and big data technologies.
• Proficient with programming languages such as Python, R, and Java, and familiar with data science frameworks and tools.
• Strong understanding of data architecture, data engineering principles, and cloud computing platforms.
• Excellent problem-solving skills with the ability to translate ambiguous business problems into structured, data-driven solutions.
• Adept at communicating complex technical concepts clearly and effectively to both technical and non-technical stakeholders.
• Strategic thinker with solid project management skills and the ability to drive end-to-end delivery of data science initiatives.
• Passionate about mentoring and developing talent, fostering a collaborative and innovative team environment.
• Knowledgeable about data privacy, security standards, and regulatory compliance related to data use.

Nice to Have

• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines for data science workflows.
• Background