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Manager Financial Pricing Analytics

Job ID 70927 Date 03/22/2017 Toronto, Canada

Scotiabank’s Decision Sciences team has a single, clear mandate – to build the next generation of analytics products by identifying, collecting, and analyzing data to distill actionable insights. The goal is to drive a better and intuitive experience for the customers, enabled by the insights. The team sits within Scotiabank’s Digital Banking organization which focuses on reimagining the experience of our customers for the digital age.

The Pricing Analytics team within Decision Sciences supports the revenue growth for each of the product business line (including lending products such as Mortgages, Lines of Credit, Loans and deposits such as Savings Accounts and GICs) through providing advanced analytical pricing solutions, and influences Scotia’s strategic decisions on consumer pricing (rates / fees).

We will provide you the opportunities to gain exposure to different businesses across the organization, a wide variety of analytical tools, an innovative work environment and expertise guidance to achieve both business and personal goals. You will be building predictive models using Python, R and SAS and working with big data stored in Hadoop and relational databases. You will also assist in designing optimization engines to recommend optimal pricing for a suite of financial products (including deposits and lending).

Key Accountabilities:

Extracting and cleansing large datasets:
Integrate data across a variety of data stores / platforms (eg. DB2, SQL server, SAS in Unix and Hive in Hadoop) for use in predictive models 
Leverage distributed computing tools (e.g. Spark, Hadoop) for analysis, data mining and modeling
Internal and external data source evaluation

Design and build predictive models that explain the customer behavior over the product life cycle:
Origination models such as response, utilization and attrition modeling, renewal models and campaign acquisition models
Portfolio segmentation
Profit or volume optimization and customer profitability forcasting
Model validation

Advances Decision Science competency:
Provide subject matter expertise on predictive modelling, data mining, statistical analysis and machine learning to Decision Science's internal customers
Effectively communicate results of highly technical projects to business audiences

Functional Competencies :

Excellent problem solving and analytical skills. Previous experience in an analyst function required
Strong programming skills, ideally in Python (C++, Java or other programming languages are also acceptable)
Solid SQL skills for querying relational databases (e.g., SAS, SQL Server, DB2, MySQL)
Experience with common statistical and machine learning libraries in Python, R, Spark is a plus
Familiarity with Hadoop Big Data ecosystem is a plus (e.g., Hive, Spark, Pig, Sqoop)
Strong theoretical knowledge and practical understanding of statistical analysis and predictive modeling
Good communication skills. Must be able to translate complex technical information to a non-technical audience
Good time management and ability to meet timelines

Educational Requirements:

Analytical background (ie  Applied Math, Statistics, Physics,  Engineering, Computer Science)
Masters or PHD in mathematics, statistics or a related discpline would be preferred


As Canada’s international bank, we are a leader when it comes to inclusion. Scotiabankers hail from over 120 countries, speak more than 100 languages and serve over 23 million customers globally. As a highly diverse company, we know that an inclusive environment for employees and customers helps everyone achieve their best. 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. Candidates selected for an interview will be contacted directly. If you require accommodation during the recruitment and selection process, please let us know. We will work with you to provide a positive recruitment experience. 

Amazing career stories begin at Scotiabank.

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