AI & ML Data Analyst for Predictive Insights

BMO U.S.; Chicago (IL); On-site; USD 65,000 - 140,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Job summary

BMO Financial Group in Chicago seeks a data science professional to mine and analyze large data sets, build predictive models, and design scalable analytics solutions to improve business decisions and customer experiences. You will collaborate with product teams, apply ML/DL techniques, and help advance data strategies across the organization while adhering to risk and ethics guidelines.

A post-secondary degree and 4–6 years of relevant experience are typical.

Qualifications

• Deep learning.
• Machine learning.
• Trust, bias and ethics.
• Creative thinking.
• Critical thinking.
• Technical proficiency gained through education and/or business experience.

Responsibilities

• Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.
• Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity.
• Collaborate with product teams and partners to understand and provide data-driven decision making, business planning and future roadmap.
• Exercises judgment to identify, diagnose, and solve problems within given rules.

Skills

Deep learning

Machine learning

Trust & Ethics

Creative thinking

Critical thinking

Verbal & written communication skills

Collaboration & team skills

Analytical acumen

Education

Post-secondary degree in related field

Job description

BMO Financial Group in Chicago seeks a data science professional to mine and analyze large data sets, build predictive models, and design scalable analytics solutions to improve business decisions and customer experiences. You will collaborate with product teams, apply ML/DL techniques, and help advance data strategies across the organization while adhering to risk and ethics guidelines.

A post-secondary degree and 4–6 years of relevant experience are typical.