Scotiabank

Senior Data Scientist, C&CA

Job description

Requisition ID: 160540

Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.

Purpose Of Job

GRM Retail Credit Risk aims to be an industry leader in developing innovative solutions for Retail Banking. This is accomplished using advanced analytics, agile principles and disciplined risk governance. To align with its departmental mission to modernize Credit Risk, the advance analytics team acts as an idea incubator and analytical use cases accelerator, leveraging non-traditional data, advance analytic algorithms and enterprise platforms. The team relies on retail credit risk expertise and key business partners to provide consulting services within GRM and help building the next generation of retail credit solutions at Scotiabank.

The Senior Data Scientist will work on key projects aimed at accelerating benefits for customers and the bank, leveraging enterprise-level data management tools and advanced analytics. She/he will work closely with Global Risk teams, the business lines, Digital Banking and IT to apply advanced analytics techniques and tools, as well as explore ideas to enhance retail and small business lending portfolios within risk appetite thresholds. The candidate will help identify and recommend opportunities to deliver innovative credit offers based on risk-reward framework and the GRM’s digital strategy.

The role requires rigorous logical thinking, curiosity, flexibility and great teamwork abilities. The candidate will be at the intersection of math/stats, computer science, communication, and domain knowledge in Risk Management, Finance or Marketing. She/he will take a leading role in agile rapid labs and risk-reward strategy development to drive innovation and digital transformation throughout the Bank and Global Risk Management.

WHAT’S IN IT FOR YOU?
  • Opportunity to make an impact in the digital transformation of Scotiabank
  • Exposure to different business lines and Caribbean markets where analytics techniques are being applied
  • Hands-on practical projects to drive innovations throughout retail credit lifecycle
  • A compensation program with competitive salary, opportunities for annual performance incentives based on performance thresholds, a competitive benefits program and continuing education programs
Job Responsibilities
  • Research, develop, and implement innovative credit solutions using big data, statistical analysis, and AI/machine learning techniques to support growth and strategy optimization opportunities within the Caribbean and Central American markets
  • Lead and drive strategy design with business partners, subject matter experts to further enhance risk-reward predictions, customer segmentation, credit limits assignment, and risk-based pricing through full credit lifecycle for retail and small business (e.g. credit origination, account management, collections strategies and/or other credit solutions)
  • Leverage Agile framework to lead, prioritize and deploy data science projects. Co-ordinate with cross-functional teams to align with project scope and meet project timelines.
  • Collaborate with Toronto and local business partners to implement new credit solutions in selected markets. Track and monitor key performance indicators to accelerate scalable deployment across key markets in an agile and rapid environment
  • Revamp existing data infrastructure and support migration to cloud
  • Work with data engineers and key stakeholders to define requirements for data ingestion, visualization technique and machine learning models to support rapid lab projects
  • Participate proactively in developing and maintaining team standards, tools and best practices
Job Requirements
  • Minimum 3 years of proven working experience in statistical analysis and/or statistical modeling roles (preferred in retail, financial, and digital industries)
  • Expert knowledge in Machine Learning techniques, such as Decision Tree, Random Forest, XGBoost, etc.
  • Ability to work with large volumes of structured and unstructured data and proficient working experience with SQL database and Hadoop ecosystem
  • Excellent programming skills in statistical modeling languages, such as SAS, Python and/or R
  • Efficient communication skills with an ability to convey complex technical concepts to non-technical audience
  • Results driven mindset with proven record of abilities to translate data and analysis to actionable insights
  • Relevant experience in risk management or related business line experience preferred
  • Knowledge of data visualization tools such as Tableau, PowerBI is a bonus
  • Excellent interpersonal skills with ability to understand and navigate team dynamics
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.

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