Senior Manager, Data Science

Key Skills

A/B Testing, Aartificial intelligence, Algorithms, Apache Hadoop, Apache Hive, Data science techniques, Design, Framework, H2O, HuggingFace, Java Programming, Machine learning techniques, Management, Mathematics, Natural Language Processing (NLP), Perl Programming, Python Programming, R Programming, SAS, SPARK Programming, SparkML, SPSS Statistics, SQL, Statistics, Terabyte scale datasets, XGBoost

Job Description

We enable and accelerate our partners on their data science and AI journeys across the Enterprise. Accelerating our teams across BMO on their path to value at scale. We help each other in times of need, and we are proud of our work. We are data practitioners, visionaries, thought leaders, multipliers, coders, and much more. Above all, we are a global team of diverse folks who enjoy working together to create smart solutions which have an impact across the enterprise.? 

We work on a diverse set of problems for diverse groups across the enterprise using state-of-the-art techniques in Computer Vision, NLP, Data Science and AI based on the relevancy and need of the business problem.? 

Being an enterprise data science team, you will always have opportunities to learn and solve interesting problems in different domains, including, Cyber Security, Capital Markets, Personal and Business Banking, Commercial Banking, Wealth Management, Financial Crime, Enterprise Risk, Legal/Audit Compliance, AIOps, HR Analytics, ESG Investing/Analysis and Climate Analytics.? 

Our Ambition is bold. It is built around putting both our capital and resources to the highest and most profitable use, with a “digital first operating model, fuelled by data-driven decisions. 

Join the Enterprise Data Science and AI team within BMO as we accelerate our path to value with: 

• Actionable insights anchored on managed Data and frictionless Analytics capabilities 
• A mindset that extends a solid core and provides a flexible edge 
• Acceleration of commercial value within a responsible framework 

Our team enables the strategic priorities of the bank, by providing progressive data capabilities, coupled with advanced analytical methods to accelerate value generation from actionable insights while operating within the bank’s full risk appetite. 

The Impact 

Senior Data Scientist, Enterprise Data Science & AI will lead strategic initiatives, build data-driven solutions that have a measurable impact, define standards, and foster knowledge sharing and collaboration in achieving our vision. 

All team members provide leadership, innovation, timely delivery, and the ability to articulate business value. Be a part of a unique opportunity to define and enable BMO's Data Science and AI vision. 

You will lead and develop solutions and capabilities for building a digitally enabled, future-ready bank with leading efficiency, profitability, and loyalty - all powered by a winning culture. 

What’s In It For You 

In this role, you will propel BMO’s Digital First strategy forward by providing business, data science, AI, and technology leadership.? 

An opportunity to apply knowledge of advanced analytic algorithms and technologies (e.g., machine learning, deep learning, artificial intelligence) to deliver better predictions and/or intelligent automation that enables smarter business decisions, improved customer experience, and drives productivity. To drive innovation through the development of Data & AI products that can be leveraged across the organization and establishes best practices. 

A leadership team that cares for your career and works to find the right opportunities for your growth. 

What We are Looking For 

• Strong Research Mindset, Coder, Integrator, Strong Execution, and Forward Thinker 
• Be relentlessly curious, take ownership, and challenge the status quo 
• Has in-depth knowledge of the data science and AI landscape as well as hands-on expertise in how to implement solutions in production environments 
• Shapes advanced conceptual thinking to solve complex or novel situations that have never been dealt with before 
• Driven partner that fosters collaborative engagements with our stakeholders

Responsibilities 

• Influences and negotiates to achieve business objectives. 
• Provides strategic input into business decisions as a trusted advisor. 
• Leads discovery process with stakeholders to identify business requirements and expected outcomes and to select relevant sources of data/information. 
• Develops the business case by identifying needs, analyzing potential options, and assessing expected return on investment. 
• Makes strategic recommendations on data collection, integration and retention requirements incorporating business requirements and knowledge of best practices. 
• Structures loosely defined and complex business problems; determines new experimentation methods and statistical techniques to design solutions. 
• Identifies/creates the appropriate algorithm to discover patterns. 
• Drives analytics innovation; poses open-ended questions, explores innovative ideas, and chooses appropriate techniques for solving business problems. 
• Applies scripting/programming skills to assemble several types of source data (unstructured, semi-structured, and structured) into well-prepared datasets with multiple levels of granularities (e.g., demographics, customers, products, transactions). 
• Develops analytical solutions by applying suitable statistical & machine learning techniques (e.g., A/B testing, prototype solutions, mathematical models, algorithms, machine learning, deep learning, artificial intelligence) to test, verify, and refine hypotheses. 
• Broader work or accountabilities may be assigned as needed and based on your career growth ambition. 

Qualifications 

• Bachelor’s / Master’s degree / Ph.D. in Computer Science, Mathematics, Physics, Engineering, Statistics, or other quantitative disciplines and/or equivalent experience. 
• Typically, 4+ years of relevant experience and/or certification in a related field of study or an equivalent combination of education and experience. 
• In-depth experience using machine learning algorithms. 
• Strong coding skills. 
• Experience with putting models into production with proper MLOps framework.? 
• Experience with distributed computing language (e.g., Hive / Hadoop/ Spark) & cloud technologies (e.g., AWS Sagemaker, AzureML). 
• Experience with programming languages (e.g., SQL, Python, R, SAS, SPSS, Perl) and machine learning /deep learning algorithms/packages (e.g., XGBoost, H2O, SparkML, Huggingface). 
• Collaboration & team skills; with a focus on cross-group collaboration - In-depth / Expert. 
• Able to manage ambiguity. 
• Data-driven decision making - In-depth / Expert.