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Data Scientist

  • Toronto, ON, Canada
  • BMOPLACE, Canada

$80,000.00 - $175,000.00 · Full-time

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Job details

Pay
$80,000.00 - $175,000.00
Job type
Full-time
Apply by
Posting language
English
Posted

Original job description

Application Deadline:

10/17/2026

Address:

33 Dundas Street West

Job Family Group:

Data Analytics & Reporting

This is a 12 month hybrid contract role in Toronto

Uses advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. Designs and constructs new processes for modeling data. Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity. Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.

  • Plays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems.
  • Work with data engineer to do data ETL.
  • Uses data mining and extracting usable data from valuable data sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data.
  • Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
  • Uses analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness.
  • Develops prediction systems and machine learning algorithms. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders.
  • Collaborate together with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap.
  • Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
  • Provides specialized consulting, analytical and technical support.
  • Exercises judgment to identify, diagnose, and solve problems within given rules.
  • Works independently and regularly handles non-routine situations.
  • Broader work or accountabilities may be assigned as needed.
  • Take measured risks while protecting the bank by applying our Risk Management Framework in the execution of your role, in line with our Risk Culture and within our approved Risk Appetite, making sound and risk informed decisions that align to business strategy, protect assets, and adhere to applicable policy documents (Frameworks, Policies, Standards, Procedures and Supporting documents), laws and regulations.

Qualifications:

Intermediate level of proficiency:

  • Mathematics, statistics & operations research.
  • Deep learning.
  • Trust, bias and ethics.
  • Creative thinking.
  • Critical thinking.

Advanced level of proficiency:

  • Fluent in SQL and Python.
  • Solid knowledge and understanding of machine learning algorithms.
  • Experience in Exploratory data analysis including feature engineering, data manipulation (required python packages: Pandas, Numpy, Scipy)  
  • Experience in building traditional machine learning models, i.e. classification, regression, clustering using Sklearn and other Python packages.
  • Big data.
  • Data visualization.
  • Computational thinking and programming.
  • Data wrangling.
  • Data preprocessing.
  • Creative reasoning.
  • Verbal & written communication skills.
  • Collaboration & team skills.
  • Analytical and problem solving skills.
  • Influence skills.
  • Data driven decision making.
  • Typically between 5 - 7 years of relevant experience and post-secondary degree in Computer Science, Computer Engineering or related field of study or an equivalent combination of education and experience.
  • Deep knowledge and technical proficiency gained through extensive education and business experience.

Salary:

$80,000.00 - $175,000.00

Pay Type:

Salaried

The above represents BMO Financial Group’s pay range and type.

Salaries will vary based on factors such as location, skills, experience, education, and qualifications for the role, and may include a commission structure. Salaries for part-time roles will be pro-rated based on number of hours regularly worked. For commission roles, the salary listed above represents BMO Financial Group’s expected target for the first year in this position.

BMO Financial Group’s total compensation package will vary based on the pay type of the position and may include performance-based incentives, discretionary bonuses, as well as other perks and rewards. BMO also offers health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. To view more details of our benefits, please visit: https://jobs.bmo.com/global/en/Total-Rewards

About Us

At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.

As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.

To find out more visit us at https://jobs.bmo.com/ca/en.

BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.

Note to Recruiters: BMO does not accept unsolicited resumes from any source other than directly from a candidate. Any unsolicited resumes sent to BMO, directly or indirectly, will be considered BMO property. BMO will not pay a fee for any placement resulting from the receipt of an unsolicited resume. A recruiting agency must first have a valid, written and fully executed agency agreement contract for service to submit resumes.

More about this job

Responsibilities

Analyze large structured and unstructured datasets using machine learning and other advanced analytical methods to identify patterns, develop predictive models, and recommend data-driven business decisions. Collaborate with data engineers, analytics professionals, product teams, and business partners to build, refine, and scale data solutions, including ETL and AI/ML applications.

Requirements

Typically requires 5–7 years of relevant experience and a post-secondary degree in computer science, computer engineering, or a related field, or an equivalent combination of education and experience. Requires advanced SQL and Python skills, knowledge of machine learning algorithms and Python data science packages, and proficiency in analytics, big data, communication, collaboration, and problem-solving.

Skills

  • SQL
  • Python
  • Machine Learning
  • Deep Learning
  • Mathematics
  • Statistics
  • Operations Research
  • Exploratory Data Analysis
  • Feature Engineering
  • Data Manipulation
  • Classification
  • Regression
  • Clustering
  • Big Data
  • Data Visualization
  • Data Wrangling

Benefits

  • Health Insurance
  • Tuition Reimbursement
  • Accident Insurance
  • Life Insurance
  • Retirement Savings Plans
  • Performance-Based Incentives
  • Discretionary Bonuses

Visa sponsorship

Not detected in the job text

Categories

  • Data & Analytics
  • Technology
  • Science & Research
  • Finance & Accounting

Keywords

  • Data Analytics
  • Data Science
  • Machine Learning
  • Deep Learning
  • Artificial Intelligence
  • SQL
  • Python
  • Pandas
  • NumPy
  • SciPy
  • Scikit-Learn
  • Exploratory Data Analysis
  • Feature Engineering
  • Data Manipulation
  • Data Engineering
  • ETL
  • Big Data
  • Predictive Modeling
  • Classification
  • Regression
  • Clustering
  • Data Visualization
  • Data Wrangling
  • Data Preprocessing
  • Trust, Bias, and Ethics
  • Risk Management
  • Business Intelligence
  • Consumer Trends
  • Data-Driven Decision Making
  • Toronto

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