Senior Manager, Personal Lending Analytics

CIBC•Toronto, ON

4d•Hybrid

About The Position

The Senior Manager, Personal Lending Analytics will be a leading contributor in the AI, Data and Analytics (AIDA) team supporting Personal Lending product lines including the Real Estate Secured Lending (RESL), Unsecured Lending and Automotive Lending businesses. The AI, Data and Analytics team focuses on creating next generation analytics assets to enable data-driven decision making for partners in Product, Marketing, Client Segment and Strategy. In this role, you will lead analytics engagements to evaluate client behaviours and optimize business decisions related to product, campaign, pricing and other business areas. You will drive innovation through advanced AI and Machine Learning solutions, translating cutting-edge technology into tangible business value and measurable outcomes. You will present insights and make data-driven recommendations to senior leaders to help identify opportunities to grow the business and better serve our clients. At CIBC we enable the work environment most optimal for you to thrive in your role. You’ll have the flexibility to manage your work activities within a hybrid work arrangement where you’ll spend 1-3 days per week on-site, while other days will be remote.

Requirements

Degree in a quantitative field (i.e. mathematics, statistics, computer science, economics, engineering, physics, business) or equivalent experience.
Demonstrated expertise in Artificial Intelligence and Machine Learning, with hands-on experience developing, deploying, and maintaining ML models in production environments.
Strong knowledge of Machine Learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn, Keras) and have applied various ML techniques including supervised/unsupervised learning, deep learning, natural language processing, and reinforcement learning.
Exceptional critical thinking, problem solving and decision-making skills, with demonstrated ability to independently identify and analyze business problems and recommend innovative solutions.
Proficient in programming languages and have experience using modern big data, analytical and dashboard tools (i.e., Python, R, SAS, SQL, Hadoop, Spark, Alteryx, Tableau, Databricks, Power BI, MLflow, Azure ML, AWS SageMaker).
Experience in building end-to-end analytics solutions involving large datasets (i.e., requirement gathering, data extraction, cleaning and transformation, statistical analysis, model development and deployment, presentation & implementation).
Working knowledge of statistical techniques (i.e., regression, time-series analysis, clustering, decision trees) and advanced Machine Learning algorithms (e.g., ensemble methods, neural networks, gradient boosting, dimensionality reduction).
Passionate about innovation and have a proven track record of translating AI/ML capabilities into measurable business value, with experience in value realization frameworks and ROI measurement.
Avid learner who recognizes the analytics field is constantly evolving.
Seek to explore emerging trends and best practices in AI, Machine Learning, and innovative analytics methodologies, and are excited to share the knowledge with others.
Very strong communication and presentation skills with a demonstrated ability to clearly and concisely present information to groups and individuals at all levels in the organization.
Put our clients first.
Engage with purpose to find the right solutions.
Go the extra mile, because it's the right thing to do.
Know that relationships and networks are essential to success.
Inspire outcomes by making yourself heard.
Bring your real self to work and you live our values – trust, teamwork and accountability.

Nice To Haves

Advanced degree is an asset (i.e. MMA, MBAN, MSc, MA, MBA).

Responsibilities

Champion a culture of innovation by identifying and implementing transformative AI and Machine Learning solutions that deliver measurable business value.
Proactively seek opportunities to leverage emerging technologies to create competitive advantages, optimize client experiences, and drive revenue growth.
Translate complex analytical initiatives into quantifiable business outcomes, demonstrating clear ROI and value realization across all engagements.
Be a leader and subject matter expert in Personal Lending.
Integrate deep domain knowledge with analytical capabilities to deliver value to stakeholders, enable data-driven decision making and proactively identify opportunities to drive business growth (projects/business cases, acquisition/retention campaigns, pricing, channels, segments, products and process enhancements).
Independently identify and leverage the right statistical techniques (descriptive, predictive, prescriptive) to extract actionable insights out of client behaviours and business trends (both internal and external).
Apply advanced Machine Learning algorithms and AI-driven methodologies to uncover hidden patterns and predict future trends with precision.
Appropriately integrate big data, business intelligence, visualization, self-service and analytical tools into engagements.
Proactively explore new applications of advanced analytics, AI, and Machine Learning to innovate and build strategic analytics assets that create sustainable competitive advantages.
Leverage big data/analytical tools to analyze large structured and unstructured datasets, build data pipelines and visualizations from multiple data sources.
Implement and deploy Machine Learning models and AI solutions using modern MLOps practices, ensuring scalability, reliability, and continuous improvement of analytical assets.
Orchestrate end-to-end delivery of solutions that meet stakeholder requirements and contribute to business success.
Think and act like an owner in analytics initiatives, ensuring the proper identification and translation of business needs into analytics requirements while maintaining a relentless focus on value creation and measurable business impact.
Find the story in data and be flexible in communicating at varying levels of detail for the right audience.
Articulate the business value and innovation potential of AI and Machine Learning initiatives to both technical and non-technical stakeholders, building enthusiasm and support for transformative change.