Data Scientist - Toronto

Scotiabank; Toronto; On-site; CAD 110,000 - 150,000; Full time

Job summary

Scotiabank seeks a Data Scientist to derive insights from data and translate them into enterprise opportunities. You will build end-to-end ML pipelines and work with analytics teams, engineering, and business lines to unlock value in a fast-paced environment.

Ideal candidates combine STEM training with production ML experience, strong programming skills (Java, C++, Python), and proficiency in ML libraries across R, Python and Spark. Collaboration and communication are essential.

Qualifications

• University degree in a STEM field (e.g., Computer Science, Engineering, Math).
• Production experience with experimental design, statistical analysis, ML and predictive modeling.
• Proficient in Java, C++ or Python; strong SQL skills in relational DBs.

Responsibilities

• Collaborate with stakeholders to identify data opportunities and ML opportunities.
• Design, build, and deploy end-to-end ML pipelines; ensure scalability and security.
• Apply statistics to large data sets and communicate results to business clients.
• Document data sources, models, and algorithms used.
• Collaborate with Data Engineering to deploy models in production.
• Present results to stakeholders and help implement data-driven changes.
• Support the analytics community with advisory, training and scalable solutions.

Skills

Curiosity

Teamwork

Flexibility

Rigorous thinking

Java

C++

Python

R

Spark

SAS

SQL

Git

Azure DevOps

CI/CD

Databricks

Airflow

Big Data

Machine Learning

Operations Research

Communication

Presentations

Education

STEM degree

Tools

SQL Server

DB2

MySQL

Job description

Requisition ID: 272873

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

Purpose

The Data Scientist role in the Analytics, Personalization & Innovation team is designed for individuals with a curiosity for deriving insights out of data and applying them to address business opportunities, in partnership with engineering teams and business lines driving innovation and advanced analytics across the Enterprise.

As part of the Advanced Analytics & Modeling team, the Data Scientist is responsible for executing and enhancing existing modeling frameworks with transparent use of enterprise-level data, AI/ML resources and advanced analytics in line with stakeholder priorities. The incumbent will support key projects in a quick pace environment, aimed at accelerating benefits for customers and the bank, leveraging enterprise-level data management tools and advanced analytics. She/he will work closely with Analytics teams, business lines and technology to apply advanced analytics techniques and tools, as well as explore ideas to enhance business opportunities utilizing advanced analytics and artificial intelligence.

Is this role right for you? In this role you will:

• Collaborate with stakeholders in identifying opportunities for leveraging data and use of ML algorithms to develop innovative solutions and solve complex business problems
• Design, develop, and implement end-to-end machine learning production pipelines (data exploration, cleaning, feature engineering, model building, and performance evaluation) and ensure that pipelines are scalable, repeatable, and secure, and can serve multiple users within the company.
• Apply statistical, analytical and programming skills to analyze and interpret large data sets and communicate results and methodologies to business clients and senior members of the analytics team.
• Prepare detailed documentation to outline data sources, models and algorithms used
• Expert in analyzing large, complex multi-dimensional datasets in structured and unstructured format.
• Leverage distributed computing tools (e.g. Spark, Hadoop) for analysis, data mining and modeling to provide actionable insights to decision makers within the Bank.
• Collaborate with Data engineering to deploy models and algorithms in production, across business lines and geographies
• Present results to business line stakeholders and help implement real data-driven changes
• Be an integral part of the Advanced Analytics community for incubating ideas and use case acceleration in all business lines through advisory, training and scalable solutions
• Support analytical use‑case delivery, as well as customer/financial benefits tracking and communication
• Creates an environment in which his/her team pursues effective and efficient operations of his/her respective areas, while ensuring the adequacy, adherence to and effectiveness of day-to-day business controls to meet obligations with respect to operational risk, regulatory compliance risk, AML/ATF risk and conduct risk, including but not limited to responsibilities under the Operational Risk Management Framework, Regulatory Compliance Risk Management Framework, AML/ATF Global Handbook and the Guidelines for Business Conduct.

Skills

Do you have the skills that will enable you to succeed in this role? - We'd love to work with you if you have:

• The Data Scientist role requires rigorous logical thinking, curiosity, flexibility and great teamwork abilities. The candidate will be at the intersection of math/stats, computer science, communication, the business line and the customer. She/he will take a supporting role in agile rapid labs and strategy development to drive innovation and digital transformation throughout the Bank and Corporate
• University degree in relevant STEM discipline (Computer Sciences, Electrical/Computer/Software Engineering and Mathematics)
• Production experience with experimental design, statistical analysis, machine learning and predictive modeling (e.g. cross-sell, upsell, attrition, acquisition and lookalike models)
• Programming skills in Java, C++ or Python
• Solid knowledge in machine Learning libraries in R, Python, Spark
• Experience with Python, SAS and SQL skills for querying relational databases (e.g. SQL Server, DB2, MySQL)
• Experience with DevOps tools (Git, Azure DevOps, CI/CD, Databricks Workflows, Airflow) and Docker concepts would be an asset
• Ability to ingest and work with large volumes of structured and unstructured non-traditional data
• Working experience with machine learning and other AI techniques for strategy design
• Working knowledge of strategy optimization leveraging operations research principles would be an asset
• Strong collaboration skills with ability to translate technical knowledge into business value
• Effective communication skills with ability to prepare project documentation and presentations

Working Conditions

This position works in a standard office environment. The position is primarily non-physical and does not involve travel. Standard working hours are a regular occurrence however depending on projects there could be some additional working hours required periodically. 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.

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.