Principal Data Scientist, Quantitative Analysis and Strategy

BMO (Bank of Montreal)•Chicago, IL

60d

About The Position

Uses advanced analytical algorithms and technologies (e.g. machine learning, deep learning, artificial intelligence) to mine and analyze large sets of structured and unstructured data to obtain insights. Designs and constructs new processes for modeling data. Develops predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity. Collaborates with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions. Plays an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems. Collaborates with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap. Collaborates with data scientists and other stakeholders to understand data and modeling needs and develop solutions that meet those needs. Designs, builds, and maintains large-scale data pipelines for reporting, analysis and machine leaning/deep leaning models. Conducts large-scale analysis of information to discover patterns and trends by combining different modules and algorithms. Develops machine learning/deep learning models. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders. Uses analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness. Fosters a culture aligned to BMO purpose, values and strategy and role models BMO values and behaviours in all that they do. Ensures alignment between values and behaviours that fosters diversity and inclusion. Regularly connects work to BMO's purpose, sets inspirational goals, defines clear expected outcomes, and ensures clear accountability for follow through.

Requirements

Advanced degree (PhD preferred) in Data Science, Statistics, Applied Mathematics, Economics, or related quantitative field.
5+ years of data science experience.
In-depth knowledge in machine learning and deep learning models, such as but not limited to, XGboosting, LSTM and LLM etc.
Data visualization and polished communication skills.
Self-driven problem solver; able to adapt and thrive in a dynamic, ambiguous, and customer-focused environment.
Highly analytical, technically proficient, and able to learn new tools and ML models quickly.
Trust, bias and ethics.
Collaboration & team skills; with a focus on cross-group collaboration.
Able to manage ambiguity.
Data driven decision making.
Experience with GenAI LLM models
Experience with MLOps, building workflows for model retraining, monitoring and deploying
Experience with ML frameworks such as TensorFlow, PyTorch
Experience with cloud-based data platforms such as AWS or Azure
Experience with data visualization tools such as Power BI

Responsibilities

Mine and analyze large sets of structured and unstructured data to obtain insights.
Design and construct new processes for modeling data.
Develop predictive models and leverages big data technology to design solutions that deliver smarter business decisions, improve customer experience, and drive productivity.
Collaborate with other data and analytics professionals and teams to optimize, refine and scale analysis into mature analytics solutions.
Play an active role in the futuristic display of data, and advancement of innovative data strategies to understand consumer trends and address business problems.
Collaborate with the product team and partners to understand and provide data-driven decision making, business planning and future roadmap.
Collaborate with data scientists and other stakeholders to understand data and modeling needs and develop solutions that meet those needs.
Design, build, and maintain large-scale data pipelines for reporting, analysis and machine leaning/deep leaning models.
Conduct large-scale analysis of information to discover patterns and trends by combining different modules and algorithms.
Develop machine learning/deep learning models. Investigates additional technologies and tools for developing innovative data solutions for business stakeholders.
Use analysis to provide recommendations and advice for business leaders to maintain to maintain market competitiveness.
Foster a culture aligned to BMO purpose, values and strategy and role models BMO values and behaviours in all that they do.
Ensure alignment between values and behaviours that fosters diversity and inclusion.
Regularly connect work to BMO's purpose, sets inspirational goals, defines clear expected outcomes, and ensures clear accountability for follow through.