Level

TD Bank

Data Scientist II

TD Bank is hiring a Data Scientist II in Toronto, Canada. It pays CAD 82k-CAD 115k a year and Level rates it ; you can apply on Level.

AI in this role

Develop agentic AI development projects, machine learning models, and advanced analytics solutions for operations.

pythonpysparksql
machine-learningpredictive-analyticsforecastingtime-series

Work Location:

Toronto, Ontario, Canada

Hours:

37.5

Line of Business:

Analytics, Insights, & Artificial Intelligence

Pay Details:

$81,600 - $115,200 CAD

TD is committed to providing fair and equitable compensation opportunities to all colleagues. Growth opportunities and skill development are defining features of the colleague experience at TD. Our compensation policies and practices have been designed to allow colleagues to progress through the salary range over time as they progress in their role. The base pay actually offered may vary based upon the candidate's skills and experience, job-related knowledge, geographic location, and other specific business and organizational needs.

As a candidate, you are encouraged to ask compensation related questions and have an open dialogue with your recruiter who can provide you more specific details for this role.

Job Description:

We are seeking motivated and curious Data Scientists to join the CPB AI2 Operations team. These roles offer the opportunity to solve complex business problems through advanced analytics and AI.

 

The successful candidates will lead analytical initiatives from business problem definition and data acquisition through analysis, modelling, visualization, stakeholder presentation, and implementation. They will work closely with operations business, risk and governance, and technology partners to translate business needs into scalable and actionable analytics and AI solutions.

 

The team is hiring for two positions at the same level, with opportunities spanning two complementary areas:

  • AI Delivery and Advanced Analytics: Supporting major agentic AI development projects, productivity analytics, colleague performance assessments, and the delivery and adoption of AI & analytics solutions.
  • Forecasting and Predictive Analytics: Developing forecasting, regression, and time-series solutions that support capacity planning, operational decision-making, and performance management.

 

Candidates are not expected to be experts in every area. Responsibilities will be aligned based on the successful candidates’ experience, technical strengths, and areas of interest.

 

Key Responsibilities include:

  • Translate business problems into practical analytics, forecasting, machine learning, or AI solutions.
  • Analyze large and complex datasets to identify trends, performance drivers, and operational opportunities.
  • Develop and maintain time-series, regression, statistical, and predictive models.
  • Use Python, PySpark, and SQL to extract, transform, validate, and analyze data.
  • Automate analytical and reporting processes to improve efficiency and accuracy.
  • Develop dashboards, visualizations, reports, and presentations using Power BI, Tableau, or similar tools.
  • Communicate analytical methods, insights, and recommendations clearly to technical and non-technical stakeholders.
  • Partner with Operations leaders, product owners, analysts, data engineers, and technology teams to deliver solutions from concept through implementation.
  • Contribute to major agentic AI initiatives and explore new applications of AI across CPB Operations.
  • Help business partners and team members understand, adopt, and effectively use new analytics and AI capabilities.

What We Are Looking For

We are looking for someone who is motivated, curious, and passionate about experimenting with new technologies, particularly AI and agentic AI. The successful candidate will be interested not only in developing new capabilities, but also in helping colleagues and business partners understand and adopt them.


You should be comfortable working independently, collaborating across teams, explaining complex concepts clearly, and connecting technical work to measurable business outcomes.


Required Qualifications and Skills

  • Undergraduate or advanced degree in mathematics, statistics, engineering, finance, economics, computer science, data science, or a related field.
  • Three or more years of relevant professional, project, or research experience.
  • Proficiency in Python and SQL for data analysis, modelling, and automation.
  • Experience with large and complex datasets, including data preparation, cleansing, validation, and analysis.
  • Experience in one or more of the following:
    • Time-series forecasting and regression modelling
    • Statistical analysis, predictive analytics, or machine learning
    • AI products, generative AI, or agentic AI applications
    • Power BI, Tableau, or similar visualization tools
    • Cloud-based data platforms and collaborative development tools such as Azure, GitHub, and Visual Studio Code
  • Strong analytical, problem-solving, communication, and data-storytelling skills.
  • Ability to manage multiple priorities and work effectively with business and technology partners.
  • Experience with financial services, banking operations, workforce analytics, or capacity planning is an asset.

 


Who We Are:

TD is one of the world's leading global financial institutions and is the fifth largest bank in North America by branches/stores. Every day, we strive to make every interaction, product, and experience remarkably human and refreshingly simple for over 27 million households and businesses in Canada, the United States and around the world. More than 95,000 TD colleagues bring their skills, talent, and creativity to foster deeper relationships, ensure disciplined execution, and build a simpler, faster banking experience. TD is deeply committed to being a leader in client experience, that is why we believe that all colleagues, no matter where they work, are client facing. Together, we are reimagining what banking can be for our clients, colleagues and communities.

Our Total Rewards Package
Our Total Rewards package reflects the investments we make in our colleagues to help them and their families achieve their financial, physical, and mental well-being goals. Total Rewards at TD includes a base salary, variable compensation, and several other key plans such as health and well-being benefits, savings and retirement programs, paid time off, banking benefits and discounts, career development, and reward and recognition programs. Learn more

Additional Information:
We’re delighted that you’re considering building a career with TD. Through regular development conversations, training programs, and a competitive benefits plan, we’re committed to providing the support our colleagues need to thrive both at work and at home.

Please be advised that this job opportunity is subject to provincial regulation for employment purposes. It is imperative to acknowledge that each province or territory within the jurisdiction of Canada may have its own set of regulations, requirements.


Colleague Development

If you’re interested in a specific career path or are looking to build certain skills, we want to help you succeed. You’ll have regular career, development, and performance conversations with your manager, as well as access to an online learning platform and a variety of mentoring programs to help you unlock future opportunities.

If you’re passionate about helping clients and building deep, lasting relationships, TD offers diverse career paths where you can grow your expertise and make a meaningful impact.  

We're committed to your success and foster a respectful workplace where diverse perspectives are valued, everyone has fair opportunities to grow, and you can unlock your full potential to achieve your career goals. Here at TD, we hire and develop the best.

Training & Onboarding
We will provide training and onboarding sessions to ensure that you’ve got everything you need to succeed in your new role.

Interview Process 
We’ll reach out to candidates of interest to schedule an interview. We do our best to communicate outcomes to all applicants by email or phone call.


Accommodation
Your accessibility is important to us. Please let us know if you’d like accommodations (including accessible meeting rooms, captioning for virtual interviews, etc.) to help us remove barriers so that you can participate throughout the interview process.

We look forward to hearing from you!

Language Requirement (Quebec only):

Sans Objet

How we rate this

Data Scientist II at TD Bank rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Machine learningPredictive AnalyticsForecastingTime SeriesPythonPysparkSQL

Also common in data scientist jobs at this level

Pay

Typical data scientist job
$168k

Use the typical data scientist figure as a reference when pay comes up. See data scientist jobs

Questions you could be asked

  1. Tell me about a project where machine learning was part of your work. What did you do?
  2. Tell me about a project where predictive analytics was part of your work. What did you do?
  3. Tell me about a project where forecasting was part of your work. What did you do?
  4. Tell me about a project where time series was part of your work. What did you do?
  5. Walk me through how you've used Python in your day-to-day work.

Adapt your resume

  • List these exact terms on your resume: Machine learning, Predictive Analytics, Forecasting, Time Series, and Python. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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