Senior Manager, Forecasting Models - Retail & Small Business
Toronto, ON, CA, M5H1H1
Scotiabank
Requisition ID: 209940
Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
The world is changing faster than ever and so are we!
“Big data”, “machine learning” and “AI” are not just buzzwords; they are an ever-increasing part of our daily life. We have decades of data powering hundreds of models deployed across a multitude of systems that are calling for smart talented team players who are results-oriented, embrace transformational challenges and relish the opportunity to help us turn our vision into reality.
Our goal is to be nothing less than The Leading Bank in The Americas by putting Customers First. Achieving this requires a Winning Team that can build, manage and govern stable high-performing models and provide our business partners with the best analytic insights and advice possible. To put things in perspective, the models that we build underpin automated risk-management decisions and forecasts that impact millions of customers and keep hundreds of billions of dollars safe every single day.
What Are We Looking For?
We want talented pragmatic analytically oriented data scientists who are equally at home interpreting and applying statistics as they are ingesting and massaging data, translating regulatory requirements into models, and explaining complex issues in simple concise ways. We want bright and energetic minds who come armed with a bottomless sense of curiosity about everything, a passion for getting things done right and a deep sense of personal and professional accountability.
To be a Senior Manager in Retail Models & Analytics, it isn’t enough to just be a great model developer; you also need to be a collaborative team player who actively listens to stakeholders and customers because you are passionate about helping them win and you need to be interested in building something lasting and great. Working with internal stakeholders across the bank to understand and translate their needs into outcomes, exploring both novel and legacy datasets and methodologies, collaborating with technology partners to get things implemented flawlessly, and monitoring, tuning up (when necessary), and governing the models that your team “owns” will all be equally important.
Make an Impact
As a Senior Manager, you will report directly to a Director and be a critical member of a team overseeing the Bank’s Retail AIRB Capital Forecasting models, interpreting the results, and developing processes to support your stakeholders. You will support – from conception through execution and governance – models covering the Bank’s retail lines (PD, LGD, EAD) that contributes to the Bank’s financial statements. You will collaborate, on a regular basis, with a wide range of stakeholders and internal partners which may include Decisioning, Provisioning, Model Operations, Enterprise Stress Testing, Model Validation and Governance, Technology & Data, Finance, Compliance and Audit.
You will have access to both traditional SAS tools and a modern machine learning stack that includes on premise GPU computing, open source Jupyter development environments, a Hadoop cluster, containerized API model deployment and data visualization business intelligence tools.
Under the guidance of your Director, you will use these tools to develop and maintain advanced risk models that will be used to support bank-wide decision making worth billions of dollars and therefore they need to be not only precise and accurate, but highly stable, explainable, compliant, secure and useful. You will be responsible for understanding the goals and priorities set for you, setting goals and priorities for your team, executing them efficiently with a perpetual eye on quality, asking questions often and delivering results in harmony with your teammates.
Is This Role Right for You?
- You believe, first and foremost, in always doing the right thing and doing things the right way
- You are both deeply curious and highly pragmatic
- You are comfortable with ambitious but realistic goals and are committed to achieving them
- You are social, engaging, not afraid to ask questions and relish the opportunity to learn from global partners across the firm (who may be less technical than you)
- You relish the opportunity and yet also understand the responsibility and weight that comes with the fact that the output of your models and analysis will directly influence the bank’s financial statements or decisions that impacts a real human being
- You are committed to quality in everything you do – statistically, process and governance wise
- You look forward to sharing your insights through high-quality verbal & written communications
- You have a genuine love, passion and talent for programming, data, and predictive modeling
- You are a dynamic and results-driven professional with a passion for leadership and mentoring
- You are professional, motivated AND FUN. We mean it.
Sample projects that you might work on include:
- Complete specialized analyses, providing data-driven recommendations and impact assessments
- Develop new, modernize and/or automate statistical solutions and recommend improvements to estimation techniques and/or models
- Collaborate with finance, data governance, technology, and compliance + audit to ensure effective governance, measurement & communication of model performance
- Conduct research of new innovative modeling methodologies, tools and regulatory requirements
- Lead the periodic monitoring, recalibration and maintenance of models and analytic tools
- Identify, promote and lead process improvements for model development, recalibration, monitoring and daily operations
- Develop or rebuild models taking into consideration all aspects about the product, business processes, data quality, integrity etc.
- Effectively document and explain the process and results in order for others to validate and implement the solution
- Ensure that the data used for model development is reliable and robust and that it adheres to industry and regulatory standards
What Do You Need to Succeed?
General
- Bachelor’s Degree in Mathematics, Computer Science, Engineering or an equivalent technical field
- A demonstrated history of analytic problem solving and sound judgment
- Experience as an analyst or data scientist with a track record of accomplishments working on cross-functional teams
- Strong English-language verbal and written communications skills: the ability to distill abstract business requirements into analysis, concisely convey technical outcomes, tell a story visually with data, prepare and edit high-quality documentation and be accepted as a trusted advisor by peers
- Able to work remotely and on-site on multiple activities simultaneously and meet deadlines
- Demonstrated track record in cultivating an environment that promotes collaboration, teamwork, and transparent communication, fostering a sense of value and engagement among team members
- Proven expertise in project management, demonstrated by a consistent track record of identifying potential risks and proactively crafting mitigation strategies to ensure the successful and timely completion of projects
Technical
- Strong fundamental understanding of statistics
- 5+ years of overall experience in analytic roles developing and using predictive, risk and/or forecasting models
- Highly proficient in 1 or more analytical programming languages (Python, R, SAS, etc.), SQL (Teradata, Oracle, DB2, SQL Server) and multiple environments (Unix & Windows)
- 1 or more years of experience with big data platforms / integration (Hadoop, Spark, Hive, Avro)
- Knowledge about credit risk models / scorecards
Nice to Haves
- Proficiency in reading, writing, and speaking Spanish
- Experience developing credit risk models / scorecards
- Domain expertise with any retail & small business banking products and/or risk management practices
- Experience training and deploying machine learning models using common Python open-source frameworks (i.e., scikit-learn) and/or Python DevOps
- Proficiency in Microsoft Office Suite (Excel, Word, PowerPoint, SharePoint, Teams and PowerBI)
What’s in It for You?
- We have an inclusive and collaborative work environment that values curiosity & ownership, encourages pragmatic creativity (i.e., true innovation), and celebrates success!
- You'll get to work with and learn from an incredibly friendly and diverse group of accomplished leaders
- Access to thousands of online and in person courses so you can brush up on skills, or learn new ones
- Multiple career paths and innumerable progression opportunities. We hire you for your talent and not just for the job. We want to see you succeed not just in your role but in your career as a whole
- A competitive rewards package that includes a base salary, a performance bonus, paid vacation, personal & sick days that start from day one, and much more!
Location(s): Canada : Ontario : Toronto
Scotiabank is a leading bank in the Americas. Guided by our purpose: "for every future", we help our customers, their families and their communities achieve success through a broad range of advice, products and services, including personal and commercial banking, wealth management and private banking, corporate and investment banking, and capital markets.
At Scotiabank, we value the unique skills and experiences each individual brings to the Bank, and are committed to creating and maintaining an inclusive and accessible environment for everyone. If you require accommodation (including, but not limited to, an accessible interview site, alternate format documents, ASL Interpreter, or Assistive Technology) during the recruitment and selection process, please let our Recruitment team know. If you require technical assistance, please click here. Candidates must apply directly online to be considered for this role. We thank all applicants for their interest in a career at Scotiabank; however, only those candidates who are selected for an interview will be contacted.
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs Avro Banking Big Data Business Intelligence Computer Science Credit risk Data governance Data quality Data visualization DB2 DevOps Engineering Excel Finance GPU Hadoop Jupyter Machine Learning Mathematics ML models Model deployment Open Source Oracle Power BI Predictive modeling Python R Research SAS Scikit-learn SharePoint Spark SQL Statistics Teradata Testing
Perks/benefits: Career development Competitive pay Home office stipend Salary bonus Startup environment Team events
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