Business Systems Analyst III

BMO•Chicago, IL

1d•Hybrid

About The Position

We are seeking a skilled, self-motivated and innovative analytics specialist with expertise in data engineering and data science, in on prem and cloud environments. The incumbent must be well versed in Python, machine learning, and have some experience working with large language models (LLMs). This role is ideal for someone who has mastered Python, operates well independently and in a team effort, thrives in a fast-paced environment and is passionate about transforming data into actionable insights and scalable analytical products to improve decision making. The work you do also contributes to making the work life of your colleagues better and more productive. It's important that you have a strong customer service mentality and be a great communicator and facilitator. The role supports an efficient and effective Compliance risk management function by designing and building automated processes, tools and analytical reporting capabilities to improve workflow, decision making and monitoring of risk and operations over time. The role does this by bringing a strong background in data engineering, data analytics, data science and statistics.

Requirements

Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, or a related field. Or a combination of higher education and 3 or more years’ direct experience in data analysis, data engineering, and machine learning.
Expert-level proficiency in Python, including base Python, Pandas, NumPy, Scikit-learn, and PyTorch/TensorFlow.
Expert level in SQL
Hands-on experience with ML Ops tools and frameworks.
Microsoft Graph API and working with APIs
Strong understanding of AWS services (e.g., S3, RDS, Lambda, Glue, Redshift, SageMaker).
Experience with orchestration tools (e.g., Apache Airflow, Prefect, LiquiBase) and ETL platforms.
Strong knowledge of Microsoft PowerBI, PowerBI Apps and Workspaces.
Experience working with fine-tuning models machine learning and generative models (e.g., OpenAI, Hugging Face Transformers, classic ML).
Excellent communication and collaboration skills.
Independent and collaborative project management skills
JIRA/Confluence
PowerBI fluency

Nice To Haves

Familiarity with Microsoft SharePoint and Microsoft PowerPlatform a plus.
GitHub CoPilot

Responsibilities

Works with various data owners to discover and select available data sources from internal sources and external vendors (e.g., trading systems, GRC, lending system, payment system, ) to fulfill analytical needs.
Supports various project teams across the project lifecycle to ensure development is aligned with the business requirements.
Recommends and implements solutions based on analysis of issues and implications for the business.
Assists in the development of strategic plans.
Identifies emerging issues and trends to inform decision-making.
Researches existing or emerging requirements & related best practices to assist and develops recommendations for changes/enhancements.
Develops informative, coherent, and usable project documents (project artifacts) for multiple stakeholders covering functional and non-functional business requirements.
Applies depth of domain & functional expertise for the assigned portfolio to drive the expected business value.
Breaks down strategic problems, and analyses data and information to provide insights and recommendations.
Builds tests cases in order to validate business requirements and End-User Testing results.
Focus is primarily on business/group within BMO; may have broader, enterprise-wide focus.
Exercises judgment to identify, diagnose, and solve problems within given rules.
Works independently on a range of complex tasks
Design, build, and maintain analytical data products, dashboards, and reports to support business decision-making.
Develop and deploy Python code to clean, process, and transform messy data.
Develop and deploy machine learning models and pipelines using Python and ML Ops best practices.
Work with orchestration and ETL tools to automate data workflows and ensure data quality and integrity.
Leverage AWS services for data storage, processing, and model deployment.
Collaborate with cross-functional teams to integrate data solutions into SharePoint, PowerPlatform and other enterprise platforms.
Explore and apply large language models (LLMs) to solve complex business problems and enhance analytical capabilities.
Monitor and optimize performance of data products and models in production environments.