OverviewThe Senior Analyst, Quantitative Analysis, Strategy and Insights in Corporate Treasury is ideal for a candidate who wants to work on developing, enhancing, implementing and maintaining quantitative models and analytics suites. They would do so by using conventional econometric and machine learning techniques for asset liability, liquidity, and interest rate risk management, customer analytics, profitability, and stress testing under various macro‐economic scenarios. This involves analyzing large account‐level and transaction‐level data, articulating the problem statement, and specifying the most appropriate quantitative solution.The successful candidate is someone who can:Effectively apply knowledge of advanced analytic algorithms and modeling techniques (e.G., large data processing, statistical modeling, machine learning) to deliver better predictions and/or intelligent automation that enables smarter business decisions, improved customer experience, and drives productivity.Confidently and clearly communicate and summarize statistical/algorithmic findings. Draw business conclusions and present actionable insight in a way that resonates with business/groups (story‐telling skills).Drive innovation through the development of Data & AI products that can be leveraged across the organization and establish best practices in alignment with Data & AI governance frameworks of BMO.Key ResponsibilitiesApply scripting/programming skills to assemble various types of source data (unstructured, semi‐structured, and structured) into well‐prepared datasets with multiple levels of granularity (e.G., demographics, customers, products, transactions).Develop agreed 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.Summarize statistical findings, draw conclusions, and present actionable business recommendations in a simple, clear way to drive action.Use appropriate algorithms to discover patterns, performing experimental design approaches to validate findings or test hypotheses.Automate and enhance processes to generate scheduled reports—detailing accurate balance sheet positions and actionable analytical insights to stakeholders efficiently and timely.Work with various data owners to discover and select available data from internal sources and external vendors to fulfill analytical needs.Document data flow, systems, and processes in data collection to improve efficiency and apply use cases.Work with stakeholders to identify business requirements,



understand distinct problems and expected outcomes; develop analytical solutions and make recommendations based on an understanding of the business strategy and stakeholder needs.Build effective relationships with internal/external stakeholders and ensure alignment. Provide advice and guidance to assigned business/groups on implementation of analytical solutions.Support development and execution of strategic initiatives in collaboration with internal and external stakeholders.Lead or participate in the design, implementation, and management of core business/group processes.Broader work or accountabilities may be assigned as needed.QualificationsTypically between 1‐2 years of relevant experience and a graduate‐level degree in a related field of study or an equivalent combination of education and experience.Experience in statistical analysis, data mining, and data cleansing/transformation.Knowledge of visualization techniques and concepts (e.G., Power BI, SpotFire).Experience with programming languages (e.G., SQL, Python, R, SAS, SPSS, MATLAB) and machine learning/deep‐learning algorithms/packages (e.G., XGBoost, H2O, SparkML).Knowledge of distributed computing and/or distributed databases; experience with distributed computing languages (e.G., Hive, Hadoop, Spark) and cloud technologies (e.G., AWS SageMaker, AzureML).Exercises judgment to identify, diagnose, and solve problems within given rules.Works independently on a range of complex tasks, which may include unique situations.Data‐driven decision making – in‐depth; verbal & written communication skills – in‐depth; collaboration & team skills – in‐depth; analytical and problem‐solving skills – in‐depth; influence skills – in‐depth; technical proficiency gained through education and/or business experience.Advanced Analytical WorkUses 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 cutting-edge data strategies to understand consumer trends and address business problems.Uses data mining and extracts usable data from valuable sources to assess feasibility of AI/ML solutions for improved processing and usage of organization data.Conducts large‐scale analysis of information to discover patterns and trends by combining different modules and algorithms.Uses analysis to provide recommendations and advice for business leaders to maintain market competitiveness.Develops prediction systems and machine learning algorithms; investigates additionaltechnologies and tools for developing innovative data solutions for business stakeholders.Collaborates with product team and partners to understand and provide data‐driven decision‐making, business planning and future roadmap.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, which may include unique situations.Broader work or accountabilities may be assigned as needed.Foundational Level of ProficiencyDeep learning.Machine learning.Trust, bias and ethics.Creative thinking.Critical thinking.Intermediate Level of ProficiencyMathematics, statistics & operations research.Big data.Data visualization.Computational thinking and programming.Data wrangling.Data preprocessing.Complex problem solving.Analytical acumen.Creative reasoning.Verbal & written communication skills.Collaboration & team skills.Analytical and problem‐solving skills.Influence skills.Data‐driven decision making.Typically between 4‐6 years of relevant experience and a post‐secondary degree in a related field of study or an equivalent combination of education and experience.Technical proficiency gained through education and/or business experience.Salary$67,200.00 – $124,200.00 (Salaried)BenefitsBMO offers a comprehensive benefits package including health insurance, tuition reimbursement, accident and life insurance, and retirement savings plans. For more details visit the BMO Total Rewards page.About UsAt BMO we are driven by a shared Purpose: Boldly Grow the Valuable in business and life. We create lasting, positive change for our customers, communities, and people. 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'll support you with the tools and resources you need to reach new milestones and broaden your skill set.BMO is committed to an inclusive, equitable, and accessible workplace. Accommodations are available on request for candidates during the selection process. To request accommodation, please contact your recruiter.#J-18808-Ljbffr

📌 Senior Analyst, Data Sciences - $67,200 - $124,200 A Year (Toronto)
🏢 BMO
📍 Toronto