Senior Data Scientist

DataJobs

Chicago (IL)

On-site

USD 90,000 - 180,000

Full time

2 days ago

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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 hiring a Senior Data Scientist to help turn large, complex datasets into predictive models and practical business insights. In this Chicago, IL onsite role, you will apply advanced analytical algorithms and AI/ML to discover patterns, support data-driven planning, and contribute to risk-aware decisions aligned with BMO’s Risk Management Framework.

What you’ll do

Use advanced analytical algorithms and technologies, including machine learning, deep learning, and artificial intelligence, to mine and analyze large sets of structured and unstructured data.
Design and build new modeling processes and develop predictive models using big data technologies to support smarter business decisions, improved customer experience, and higher productivity.
Perform large-scale analysis by combining modules and algorithms to uncover trends and patterns across information sources.
Collaborate with other data and analytics professionals to optimize, refine, and scale analytics solutions into mature capabilities.
Engage in data-focused innovation to advance strategies for understanding consumer trends and solving business problems.
Conduct data mining and extraction from valuable sources to evaluate feasibility of AI/ML approaches and improve processing and usage of organizational data.
Develop prediction systems and machine learning algorithms, and investigate additional technologies and tools to create innovative solutions for business stakeholders.
Provide specialized consulting, analytical, and technical support, including recommendations and advice to business leaders to help maintain market competitiveness.
Work with product teams and partners to support data-driven decision making, business planning, and future roadmaps.
Operate primarily within a business/group focus, with potential for broader enterprise-wide impact.
Use judgment to identify, diagnose, and solve problems within defined rules; work independently and manage non-routine situations.
Apply BMO’s Risk Management Framework in a way consistent with Risk Culture and approved Risk Appetite, making sound, risk-informed decisions aligned with business strategy, protecting assets, and complying with applicable policies, laws, and regulations.

Required experience and skills

Mathematics, statistics & operations research.
Deep learning.
Machine learning.
Trust, bias and ethics.
Creative thinking and critical thinking.
Big data.
Data visualization.
Computational thinking and programming.
Data wrangling and data preprocessing.
Creative reasoning.
Verbal and written communication skills, collaboration and team skills.
Analytical and problem solving skills, influence skills, and data-driven decision making.
Typically 5 to 7 years of relevant experience plus a post-secondary degree in a related field, or an equivalent combination of education and experience.
Deep technical proficiency demonstrated through extensive education and business experience.

Technologies

machine learning
deep learning
artificial intelligence
big data
data visualization

Compensation and benefits

Salary range: USD 90,000 to 180,000 per year (salaried). Compensation may vary based on factors such as location, skills, experience, education, and qualifications, and may include commission structure for eligible roles. Total compensation can include performance-based incentives, discretionary bonuses, and other perks and rewards.