Purpose:

The successful candidate will be part of a dynamic, innovative team that supports the Marketing Analytics & Product functions within Scotiabank’s Canadian Bank Analytics group. The individual will develop statistical models, data-mining and analytical solutions to solve a wide array of business problems, including how to drive acquisition, migration and engagement strategies across our customer base.

Scotiabank provides a collaborative work environment where you get to see end-to-end how your work can shape and define strategies. We will provide you the opportunities to gain exposure to different businesses across the organization, a wide variety of analytical tools that will allow you to build complex decision engines and predictive models, work with big data, structured and un-structured.

What will you do in this role?

Design and integrate customer segmentation, channel analytics, campaign optimizations and recommendation/decision engines to help elevate our customer’s experiences across various channels and move to a personalized 1:1 customer journey

Synthesize data across multiple platforms to identify trends and deliver key insights and business recommendations around a customer-first approach to driving engagement and results across our marketing channels and campaigns, to then bringing these recommendations to market through execution and measurement

Act as a modelling and analytics generalist, provide subject matter expertise on modelling/segmentation, advanced analytics, data mining and statistical analysis

Ability to validate and measure effectiveness of customer/channel/campaign strategies to continually make ongoing changes and improvements

Supporting key information technology initiatives, such as enhancements in single view of customer, customer/ channel data warehouse, CRM and campaign management

Effectively communicate results of highly technical projects to stakeholders and deliver high quality, high impact analytical solutions to business problem

Do you have the skills that will enable you to succeed?

Analytical background: preferably Master or PhD degree with a quantitative focus, such as statistics, applied mathematics, economics, computer science

5 years of related experience needed, preferably within a financial, retail or consulting industry, customer segmentation and channel analytics an asset

Demonstrated experience of developing and implementing statistical models (predictive & descriptive) and advanced analytics

Hands-on experience with Python and SAS

Experience with relational databases and solid SQL skills (SQL Server, DB2, MySQL)

Experience with Bash/Unix Shell Scripts with Python/Docker/Airflow used for automating tasks

Familiar with container-based deployments using Docker, working with Docker images, Docker Hub and Docker-registries and Kubernetes.

Familiar with Hadoop Big Data ecosystem (Hive, Spark, Pig, Sqoop) an asset.

Demonstrated experience developing and implementing recommendation engines in a multi-channel marketing environment an asset

Strong business acumen: understanding of business and financial models and ability to link communication tactics to strategic objectives

Self-motivated, strong quantitative skills, attention to detail, a high aptitude for problem solving and a natural interest in understanding customer behavior