Senior Data Scientist - ML, AI & Big Data Analytics

DataJobs; Chicago (IL); On-site; USD 90,000 - 180,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Performance-based incentives

Discretionary bonuses

Other perks and rewards

Job summary

BMO Financial Group is seeking a Senior Data Scientist for an on-site role in Chicago, IL. You will apply advanced analytics, machine learning, and AI to turn large datasets into predictive models and actionable business insights, aligned with BMO's Risk Management Framework.

Responsibilities include building models, mining data, and collaborating with analytics teams to scale solutions and influence risk-aware decisions for business leaders.

Qualifications

• Mathematics, statistics, and operations research fundamentals.
• Deep learning and machine learning proficiency.
• Experience with data visualization and data wrangling.

Responsibilities

• Apply advanced analytics, ML, and AI to mine large structured and unstructured data.
• Design and build predictive models using big data technologies to inform decisions.
• Collaborate with data and analytics teams to scale analytics capabilities.
• Provide consulting and analytical support to business leaders for data-driven decisions.
• Work with product teams to support data-driven planning and roadmaps.

Skills

Mathematics & statistics

Deep learning

Machine learning

Trust & ethics

Creative thinking

Big data

Data visualization

Programming

Data wrangling

Analytical thinking

Communication

Problem solving

Experience 5-7 years

Education

Post-secondary degree in related field

Tools

None

Job description

BMO Financial Group is seeking a Senior Data Scientist for an on-site role in Chicago, IL. You will apply advanced analytics, machine learning, and AI to turn large datasets into predictive models and actionable business insights, aligned with BMO's Risk Management Framework.

Responsibilities include building models, mining data, and collaborating with analytics teams to scale solutions and influence risk-aware decisions for business leaders.