Manager, Financial Pricing Analytics

Scotiabank   •  

Toronto, ON

Not Specified years

Posted 239 days ago

This job is no longer available.

About the Manager, Financial Pricing Analytics

The Pricing Analytics team within Decision Sciences supports the revenue and volume growth for each of the product business line (including lending products such as Mortgages, Lines of Credit, Credit Cards, 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) and other consumer behaviour initiatives.

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, PySpark and SAS and working with big data stored in Hadoop and relational databases.

You will also have exposure to Cloud computing (Microsoft Azure or Google cloud). In addition, you will assist in designing optimization engines to recommend optimal pricing for a suite of financial products (including deposits and lending).

What will you do in this role?

  • You will extract and cleanse large datasets:
  • Integrate data across a variety of data stores / platforms (eg. DB2, SQL server, SAS in Unix and Hive in Hadoop) in a way that helps building advanced analytical models
  • Leverage distributed computing tools (e.g. Spark, Hadoop) for analysis, data mining and modeling
  • Explore data sourced from other environments including (but not limited to) the data lake; apply newly available data to pricing problems (ie. flow of funds, transcribed calls, network analytics data etc.)
  • Internal and external data source evaluation
  • You will design and build predictive models that explain the customer behavior over the product life cycle:
  • Origination models such as response, utilization and attrition modeling
  • Portfolio management models such as renewal models, re-pricing models, credit limit optimization, balance transfer and campaign acquisition models  
  • Portfolio segmentation/customer sensitivity modeling
  • Performing revenue optimization for a chosen portfolio. You need to understand business objectives, translate them into mathematical optimization problems, create profit function and recommend optimal pricing for each product
  • Create and apply model and algorithm testing strategies to conduct multi-variate testing and A/B testing to measure effectiveness of models and make ongoing changes
  • Model validation
  • You will advance the Decision Science competency:
  • Collaborate with business lines and other stakeholders and identify opportunities to drive business value and influence future pricing strategy by leveraging Data Science
  • 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

Are you the right person for this role?

  • You have excellent problem solving and analytical skills (previous experience in an analyst function is required)
  • You have good communication skills, and you can translate complex technical information to a non-technical audience
  • You have good time management skills and are able to meet timelines

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

  • You have an analytical background (Applied Math, Statistics, Physics, Engineering, Computer Science)
  • It would be great if you also held a Masters or PHD in mathematics, statistics or a related discpline
  • You have strong programming skills, ideally in Python or R (C++, Java or other programming languages would also be great)
  • You have solid SQL skills for querying relational databases (SAS, SQL Server, DB2, MySQL)
  • You have strong theoretical knowledge and practical understanding of statistical analysis and predictive modeling

It would be great if you also:

  • Have experience with common statistical and machine learning libraries in Python, R, Spark (Keras/Tensorflow, Sklean)
  • Are familiar with HadoopBig Data ecosystem (Hive, Spark, Pig, Sqoop)
  • Are familiar with Cloud computing (Microsoft Azure or Google cloud)

What's in it for you?

  • We have an inclusive and collaborative working environment that encourages creativity, curiosity, and celebrates success!
  • We provide you with the tools and technology needed to succeed 
  • You'll get to work with and learn from diverse industry leaders
  • We offer a competitive total rewards package that includes a base salary, a performance bonus, company matching programs (on pension & profit sharing), 4 weeks of vacation, personal & sick days, paternity/maternity leave top-ups and much more.
  • If you’re interested in helping us shape the future of banking, click the “Apply now” button to submit your application. We are hiring for a variety of high impact technical roles (design/agile/full stack/DevOps). If you are curious but aren’t sure this role is right for you please contact us anyway - we’re moving fast and looking for hard-working and innovative individuals to take us to the next level.

Requisition ID: 19476