At a Glance
- Tasks: Transform complex financial data into actionable insights using AI and analytics.
- Company: Join TD, a leading global financial institution with a focus on innovation.
- Benefits: Competitive salary, health benefits, career development, and flexible work options.
- Other info: Collaborative environment with opportunities for growth and skill development.
- Why this job: Shape the future of finance analytics and make a real impact with AI solutions.
- Qualifications: 3+ years in data science or AI, strong Python and SQL skills required.
The predicted salary is between 81600 - 115200 $ per year.
Help shape the next generation of Finance analytics and AI at TD. Join Finance AI2 to turn complex financial data into actionable insights and build responsible, scalable AI and analytics solutions that help Finance teams make informed decisions. You will work with Finance business partners, TD Data teams, and technology stakeholders to identify high-value opportunities and translate them into trusted solutions. As a Data Scientist, you will help design, develop, test, and operationalize generative AI, Copilot, and agentic solutions for Finance. The role combines AI solution development, prompt and context engineering, data preparation, evaluation, business insight, and stakeholder adoption. You will also contribute to the support and modernization of existing analytics workflows as the team transitions toward strategic platforms and reusable AI capabilities.
Key Accountabilities
- Partner with Finance stakeholders to understand business challenges, identify high-value opportunities, and translate impactful questions into practical analytics and AI solutions.
- Identify Finance use cases where generative AI, Copilot, or agentic solutions can improve decision-making, productivity, or user experience.
- Design, prototype, test, and operationalize AI-powered solutions using approved enterprise platforms and trusted data sources.
- Develop reusable agent capabilities, prompts, instructions, context, grounding approaches, and workflow integrations.
- Define and apply evaluation methods for solution quality, accuracy, reliability, business relevance, and user adoption.
- Prepare semantic models, metadata, and data foundations required for reliable AI and Copilot experiences.
- Partner with business, TD Data, technology, risk, and governance stakeholders to move solutions from concept through controlled implementation.
- Monitor deployed solutions, investigate issues, incorporate user feedback, and continuously improve performance.
- Analyze complex datasets and use effective data visualization and storytelling to communicate insights, implications, and recommendations.
- Support and modernize existing analytics and Alteryx workflows where required to maintain business continuity.
- Collaborate across analytics, data, technology, and business teams to deliver sustainable solutions and strengthen knowledge-sharing.
Required Qualifications And Skills
- 3+ years of relevant experience in data science, advanced analytics, AI engineering, machine learning, or a related field.
- Hands-on experience designing or developing generative AI, Copilot, or agentic solutions that address business problems.
- Strong Python or PySpark and SQL skills for data preparation, solution development, integration, testing, and analysis.
- Experience with prompt engineering, context design, retrieval or grounding techniques, and evaluation of AI-generated outputs.
- Experience integrating AI solutions with enterprise data, APIs, tools, workflows, or analytics products.
- Understanding of responsible AI, privacy, security, model risk, human oversight, and controlled deployment.
- Experience analyzing complex datasets and translating technical findings into actionable business recommendations and data-driven decisions.
- Strong business acumen, experimentation, problem-solving, data storytelling, communication, and stakeholder-management skills.
- Ability to independently own assignments from problem definition through implementation, validation, operationalization, and handoff.
- Undergraduate degree in computer science, engineering, mathematics, statistics, finance, or a related field, or equivalent practical experience.
- Experience with Databricks, Microsoft Copilot, Copilot Studio, Power BI, semantic models, or comparable AI and data platforms is considered a strong asset.
- Finance, accounting, banking, or broader financial-services experience is considered a strong asset.
- Experience with Alteryx development, production support, or workflow modernization is considered a strong asset.
Additional Information
- Work independently within a specialized analytics function and provide technical guidance where required.
- Apply technical expertise and business acumen to complex operational issues and cross-functional initiatives.
- Balance AI solution development, business insight generation, stakeholder partnership, analytics modernization, and project delivery priorities.
- Contribute to a collaborative team environment through experimentation, cross-training, knowledge transfer, and shared delivery standards.
- Generally reports to a Manager or Senior Manager.
Data Scientist II employer: TD
TD Securities is an exceptional employer located in Toronto, Ontario, offering a dynamic work environment that prioritizes innovation and professional growth. With a strong commitment to employee development, competitive compensation, and a comprehensive benefits package, TD fosters a culture of collaboration and inclusivity, empowering colleagues to thrive both personally and professionally. Join a forward-thinking team where your contributions are valued, and you can make a meaningful impact in the capital markets sector.
