Position Description

CGI is seeking a professional to design, develop, and deploy scalable AI/ML solutions that solve complex business challenges within a highly regulated financial services environment. This role is responsible for the complete machine learning lifecycle, including problem formulation, data preparation, model development, application engineering, deployment, monitoring, and operational support.

We partner with 15 of the top 20 banks globally, and our top 10 banking clients have worked with us for an average of 26 years!

This role is located at a client site in Washington, DC. A hybrid working model is acceptable.

Your future duties and responsibilities

The ideal candidate combines strong data science expertise with software engineering and MLOps capabilities to build production-ready AI/ML applications. Working closely with business stakeholders, engineering teams, and cloud platform teams, this individual will develop reliable, scalable solutions leveraging AWS-based technologies and modern machine learning practices.

Key responsibilities include:

Building and maintaining machine learning models.
Developing data pipelines and model-driven applications.
Implementing monitoring and governance controls.
Ensuring solutions meet performance, compliance, and operational requirements.

Required qualifications to be successful in this role

5+ years of hands-on experience developing and deploying production-ready machine learning models and AI applications, including experience supporting solutions in production environments through MLOps practices.
Strong experience designing and deploying machine learning and AI solutions in production environments.
Advanced Python development skills, including experience building maintainable, scalable applications and data pipelines.
Solid background in statistical modeling, predictive analytics, and machine learning algorithms.
Experience working with AWS cloud services such as SageMaker, S3, Redshift, and related compute services.
Hands-on knowledge of MLOps practices including model deployment, version control, CI/CD, monitoring, and retraining strategies.
Proficiency with data processing and analytics tools including Pandas, NumPy, Scikit-learn, TensorFlow, and PySpark.
Strong SQL skills and experience working with large-scale datasets and distributed processing frameworks.
Experience developing real-time and batch-processing AI/ML applications and services.
Understanding of model performance monitoring, data drift detection, and operational reliability best practices.
Familiarity with model governance, validation, auditability, and documentation requirements common in financial services organizations.
Strong analytical thinking, problem-solving ability, and communication skills.
Ability to collaborate effectively with data engineers, software developers, cloud architects, and business stakeholders.

Desired Skillset

Master's degree in a related discipline preferred.
Relevant cloud or machine learning certifications (AWS Certified Machine Learning, AWS Certified Solutions Architect, etc.) are beneficial but not required.

Education

Bachelor's degree in Data Science, Statistics, Computer Science, Engineering, Mathematics, or a related quantitative field required.

Compensation and Benefits

A reasonable estimate of the current range for this role in the U.S. is $111,600.00 - $154,300.00.

CGI's benefits are offered to eligible professionals on their first day of employment to include:

Competitive compensation
Comprehensive insurance options
Matching contributions through the 401(k) plan and the share purchase plan
Paid time off for vacation, holidays, and sick time
Paid parental leave
Learning opportunities and tuition assistance
Wellness and Well-being programs

What you can expect from us

Together, as owners, let's turn meaningful insights into action. Life at CGI is rooted in ownership, teamwork, respect and belonging. You are invited to be an owner from day 1 as we work together to bring our Dream to life. You'll develop innovative solutions, build relationships, and shape your career by joining a company built to grow and last.

Full Stack Data Scientist

Job summary

Work model