What You’ll Do
You'll consult with data scientists, the data and analytics teams, technology partners, business partners to create pipelines, governance and solutions that impact a variety of model ops, data and insight challenges across the North American Commercial Bank. You’ll wrap model ops and analytics in clean, repeatable, and automated processes. You’ll play a critical role in elevating business stakeholders’ confidence in our data. More specifically you will:
- Become the expert on the data sourced and used in the ML operations
- Transform structured and unstructured data for ML and Analytics programs.
- Ensure production behavioral scores and business metrics values align with expectations
- Identify and explain deviations in metrics proactively. Set in motion paths for resolution
- Exercises judgment to identify, diagnose, and solve problems within given rules
- Clarify key business metrics. Code and implement these metrics at scale
- Prepare modeling master data sets in collaboration with data scientists
- Create insights and visualizations which answer high impact business questions
- Prepare model validation documentation
Qualifications
- Consultative approach in engaging internal partners (e.g. data science, business, technology) desired
- Strong creative reasoning and computational thinking skills
- Clear verbal & written communication skills
- Extensive collaboration & team skills
- Experience impacting business transformation with data
- Proven experience building data pipelines in production for advanced analytics use cases
- Practical knowledge of software engineering concepts and best practices, inc. DevOps, DataOps, and MLOps
- Proven ability to write clean, maintainable, scalable, and production ready code
- Experience utilizing NLP to transform Unstructured Data
- Strong proficiency with SQL and its variations among different databases
- 4+ years production development experience
- 6+ years of relevant work experience as a Data Operations Engineer
- 6+ years of hands-on experience in building production ETL/ELT solutions for large scale data pipelines
- Familiarity with distributed computing frameworks (e.g. Spark, Dask), and analytics libraries (e.g. pandas, NumPy, matplotlib)
- Familiarity with Generative AI use, optimization, and tools (APIs, Vector DBs, Prompt Engineering)
- Familiarity with cloud platforms (e.g. AWS, Azure, GCP)
- 6+ years of relevant experience and post-secondary degree in related field of study or an equivalent combination of education and experience
Salary: $79,800.00 - $148,000.00
Pay Type: Salaried
We’re here to help
At BMO we are driven by a shared Purpose: Boldly Grow the Good in business and life. It calls on us to create lasting, positive change for our customers, our communities and our people. By working together, innovating and pushing boundaries, we transform lives and businesses, and power economic growth around the world.
As a member of the BMO team you are valued, respected and heard, and you have more ways to grow and make an impact. We strive to help you make an impact from day one – for yourself and our customers. We’ll support you with the tools and resources you need to reach new milestones, as you help our customers reach theirs. From in-depth training and coaching, to manager support and network-building opportunities, we’ll help you gain valuable experience, and broaden your skillset.
BMO is committed to an inclusive, equitable and accessible workplace. By learning from each other’s differences, we gain strength through our people and our perspectives. BMO is an equal opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. Accommodations are available on request for candidates taking part in all aspects of the selection process. To request accommodation, please contact your recruiter.
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