Senior Data Science Specialist — AI/ML for Credit Risk

BMO; United States; On-site; USD 142,000 - 166,000; Full time

Benefits offered by this job

Health insurance

Tuition reimbursement

Accident and life insurance

Retirement savings plans

Job summary

BMO Financial Group seeks a Specialist III-IC Data Sciences to apply advanced analytics, ML, and AI to large data sets. You will build predictive models, design scalable data processes, and collaborate with analytics teams to improve decision making and customer experiences.

The role emphasizes data mining, model development, and feasibility analysis of AI/ML solutions for banking applications, with a strong focus on credit risk and big data tooling.

Qualifications

• Bachelor's degree in Mathematics, Statistics, Applied Analytics, Actuarial Science, Operations Research or related quantitative field (foreign education accepted) plus 5 years experience in credit risk models and data manipulation.
• Master's degree in Mathematics, Statistics, Applied Analytics, Actuarial Science, Operations Research or related quantitative field (foreign education accepted) plus 3 years experience in credit risk models and data manipulation.
• Experience includes 3 years data preparation/analysis using SQL, SAS, R, Python, Tableau; 3 years building risk models for consumer/commercial credit; in-depth analysis of credit bureau data.

Responsibilities

• Mine and analyze large structured and unstructured data to obtain insights.
• Develop predictive models and leverage big data technologies to design solutions.
• Collaborate with data analytics teams to operationalize analytics into scalable solutions.
• Explore AI/ML feasibility and experiment with new data technologies for business impact.

Skills

SQL

SAS

R

Python

Tableau

Credit risk models

Data analysis

Education

Bachelor's degree

Master's degree

Job description

BMO Financial Group seeks a Specialist III-IC Data Sciences to apply advanced analytics, ML, and AI to large data sets. You will build predictive models, design scalable data processes, and collaborate with analytics teams to improve decision making and customer experiences.

The role emphasizes data mining, model development, and feasibility analysis of AI/ML solutions for banking applications, with a strong focus on credit risk and big data tooling.