Data Scientist, Tax Transformation Office
$64,000–$96,000 year
Hybrid · Toronto, Ontario, Canada
Job Summary
Data Scientist in the Tax Transformation Office leading AI/ML initiatives within the Tax R&D Lab to prototype, build, train, and scale intelligent solutions across Tax operations. Focus areas include NLP, generative AI, knowledge graphs, predictive analytics, and automation to modernize workflows, improve efficiency, and enhance client outcomes. The role involves rapid experimentation, prototyping, and productionizing AI-enabled workflows, collaborating closely with Transformation Relationship Managers, Tax practitioners, Data & Analytics, I&C, and leadership teams, and bridging strategy with technical execution in cloud environments.
Required Qualifications
- Master’s degree or PhD in Computer Science, Data Science, Machine Learning, AI, or related quantitative discipline preferred
- 3+ years of experience building and deploying machine learning or AI solutions in production environments
- Strong proficiency in Python and modern data science libraries including Pandas, NumPy, Scikit-Learn, TensorFlow, or PyTorch
- Experience with NLP, generative AI, LLMs, vector databases, embeddings, or knowledge graph technologies preferred
- Experience with SQL and NoSQL databases and scalable data architectures
- Familiarity with cloud platforms such as Azure, AWS, or GCP
- Experience with MLOps, model deployment, APIs, and scalable AI infrastructure considered an asset
- Strong communication skills with ability to explain technical concepts to non-technical stakeholders
- Experience working in transformation, consulting, innovation, or business-facing environments considered an asset
- Ideal Candidate Will Have Strong business curiosity and problem-solving mindset
- Ability to balance experimentation with scalable execution
- Strong collaboration and stakeholder engagement skills
- Interest in workflow modernization, intelligent automation, and future-state operating models
- Comfort operating in fast-paced and evolving transformation environments
- Passion for continuous learning and emerging technologies
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