Purpose of Job:
The Data Science and Analytics team has been focused on building out a library of sophisticated models and the requisite infrastructure to enhance data driven decision making across the bank.
We combine the latest optimization, mathematical modeling and machine learning technologies with our extensive network of partners to design and implement innovative solutions for solving business challenges.
We are seeking a high performance, enthusiastic professional with experience in advanced analytics, integer optimization, statistical modeling, and machine learning algorithms.
The incumbent works with staff having diverse technological education/experience and recommends innovations while maintaining focus on implementing actionable models and driving business value.
• Deliver high-quality innovative modeling solutions to support optimization modeling in several verticals
• Work closely with researchers at top academic institutions in Canada and the United States to develop leading solutions for complex optimization and machine learning challenges
• Design and develop big data applications for implementing predictive analytics and machine learning algorithms, with the goal of discovering valuable insights from available data
• Develop and support the bank's cash flow and correspondent banking network optimization models through developing algorithms to optimize flow and the requisite graph and network infrastructure to support complex analysis
• Support models designed to optimize financial resources including balance sheet, capital, funding and liquidity
• Provide consultative support to management. Thus, excellent written communication skills are also essential for preparing proposals, management reports, and responding to field queries.
• Develop, test and maintain statistical predictive models using data science techniques (including linear and logistic regression, neural networks, decision trees, experimental design) testing, implementation, scoring and monitoring. Including supervised and unsupervised learning, boosting and ensemble methods.
• 2+ years of experience working as an applied data scientist or equivalent practical experience.
• 4+ years of experience in advanced analytics, integer optimization, statistical modeling, and machine learning algorithms including supervised and unsupervised learning, boosting and ensemble methods to discover hidden insights within the data.
• Experience with optimization packages (Cplex, GAMS, LINGO, etc.)
• Experience with data extraction, manipulation and analysis from multiple sources using SQL, noSQL, SAS, or Hadoop.
• Experience with data visualization through third-party API integration (e.g., Google charts, D3/C3, High chart, Tableau).
• 4+ years of experience with Python, R or Spark.
• Working well with time sensitive deadlines
• Team player mentality
• Sense of pride and ownership over the quality of their work
• Sense of humor
Advanced degree in Operations Research, AppliedStatistics, Computer Science or related field
Relevant research experiencepreferred
Requisition ID: 21495