Principal Data Scientist

BMO Financial; Chicago (IL); Hybrid; USD 122,000 - 228,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Performance-based incentives

Job summary

BMO Financial Group is seeking a Principal Data Scientist in Chicago, hybrid. You will build predictive, ML, and deep learning models to influence business decisions and scale analytics across the organization.

You will design data processes, deploy scalable analytics, and collaborate with partner teams on data strategies, consumer trends, and business outcomes.

Qualifications

• 5+ years of data science experience required.
• Advanced degree in a quantitative field (PhD preferred).
• Experience with ML/DL modeling, GenAI and LLMs, and cloud platforms.

Responsibilities

• Design and build predictive, ML, and DL models to support business decisions.
• Develop and scale data pipelines for reporting and analytics.
• Collaborate with cross-functional teams to operationalize analytics solutions.

Skills

Data science experience

Education

Advanced degree (PhD preferred)

Tools

TensorFlow

PyTorch

XGBoosting

LSTM

GenAI LLM models

MLOps

Job description

The Principal Data Scientist at BMO Financial Group applies advanced analytical algorithms and big data and AI to uncover value in both structured and unstructured information. This hybrid role is based in the Chicago office and focuses on building predictive, machine learning, and deep learning models that support business decision-making across the organization.

In this position, you will shape modeling and data processes, scale analytics solutions with partner teams, and contribute to evolving data strategies tied to consumer trends and business outcomes. The salary range for this salaried role is USD 122,400 - 228,000 per year.

What you'll do

• Use machine learning, deep learning, and artificial intelligence to mine and analyze large volumes of structured and unstructured data for actionable insights.
• Design and construct new approaches for modeling data.
• Develop predictive models and use big data technology to deliver solutions that improve business decision quality, customer experience, and productivity.
• Collaborate with data and analytics professionals to optimize, refine, and scale analytics into mature solutions.
• Contribute to innovative data strategies focused on understanding consumer trends and addressing business problems.
• Work with the product team and partners to support data-driven decision-making, business planning, and future roadmap discussions.
• Partner with data scientists and stakeholders to identify data and modeling needs and develop solutions aligned to those needs.
• Design, build, and maintain large-scale data pipelines to support reporting, analysis, and machine learning/deep learning models.
• Conduct large-scale analysis to identify patterns and trends by combining modules and algorithms.
• Develop machine learning and deep learning models and investigate additional technologies and tools for innovative data solutions.
• Use analysis to provide recommendations and guidance to business leaders for maintaining market competitiveness.
• Role-model BMO values and behaviors, connect work to BMO's purpose, set inspirational goals, define expected outcomes, and ensure accountability for follow-through.
• Ensure alignment between values and behaviors that supports diversity and inclusion.

What you bring

• 5+ years of data science experience.
• An advanced degree (with PhD preferred) in Data Science, Statistics, Applied Mathematics, Economics, or a related quantitative field.
• In-depth knowledge of machine learning and deep learning models, including examples such as XGBoosting, LSTM, and LLM.
• Experience with GenAI LLM models.
• Trust, bias, and ethics awareness.
• Experience with MLOps, including building workflows for model retraining, monitoring, and deployment.
• Experience with machine learning frameworks such as TensorFlow and PyTorch.
• Experience with cloud-based data platforms such as AWS or Azure.
• Data visualization and polished communication skills, including experience with Power BI.
• Collaboration and team skills with a focus on cross-group collaboration.
• Ability to manage ambiguity and make data-driven decisions.

Technologies

• Machine learning, deep learning, artificial intelligence
• XGBoosting, LSTM, LLM
• GenAI LLM models
• MLOps
• TensorFlow, PyTorch
• AWS, Azure
• Power BI

Benefits

• Health insurance
• Tuition reimbursement
• Accident and life insurance
• Retirement savings plans
• Performance-based incentives, discretionary bonuses, and other perks and rewards

Job family group: Data Analytics & Reporting
Pay type: Salaried
Location: Chicago, IL (hybrid)