Data Scientist II
About The Position
The Analytics, Insights & Artificial Intelligence (AI2) team helps transform data into actionable insights that support strategic decision-making across TD. Within AI2, the Canadian Commercial Banking (CCB) team partners with business leaders, analytics professionals, and technology teams to deliver reporting, advanced analytics, and AI solutions that help drive growth, improve customer experiences, and support sound risk management. As part of our team, you'll have the opportunity to work on meaningful business challenges, leverage modern analytics technologies, and contribute to data-driven solutions that support commercial banking customers across Canada. As a Data Scientist II, you'll work alongside colleagues and partners to transform data into insights and solutions that help the business make better decisions. You'll gain hands-on experience with data science, and business analytics while building a strong foundation for your career.
Requirements
- Undergraduate degree in Statistics, Mathematics, Computer Science, Engineering, Economics, Data Science, Finance, or a related quantitative field
- 2+ years of relevant experience in analytics, data science, machine learning, or a related discipline
- Strong analytical and problem solving skills
- Ability to learn quickly and work in a fast-paced environment
- Strong communication and collaboration skills
- Ability to manage multiple priorities and meet deadlines
- Curiosity and a passion for using data to solve business problems
- Experience using Python and SQL for data analysis and data manipulation
- Familiarity with analytics python libraries
- Understanding of analytics and data exploration methodologies
- Experience working with structured datasets and relational databases
- Experience creating reports, dashboards, or visualizations using tools such as Power BI or Tableau
- Knowledge of data quality and validation practices
Nice To Haves
- Internship, co-op, research, or project experience in data science, analytics, or relevant field
- Experience with cloud-based platforms such as Microsoft Azure
- Familiarity with PySpark
- Knowledge of Banking or Financial Services
Responsibilities
- Explore and analyze large datasets to identify trends, patterns, and opportunities
- Translate business questions into structured analyses and actionable recommendations
- Develop reports, dashboards, and performance insights for business partners
- Develop datasets, queries, and analytical assets using Python, SQL, and enterprise data platforms
- Contribute to automating reporting processes and data pipelines
- Support the development and testing of machine learning and predictive analytics solutions
- Collaborate with business stakeholders, data engineers, and senior data scientists
- Help define analytical requirements and translate business needs into technical solutions
- Present findings and recommendations to a variety of audiences
- Apply data validation and quality control processes to ensure accuracy and reliability
- Support governance, risk, and control requirements related to analytics and AI solutions
- Contribute to the continuous improvement of analytics processes and best practices
Benefits
- health and well-being benefits
- savings and retirement programs
- paid time off
- banking benefits and discounts
- career development
- reward and recognition programs
- training programs
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
