Requisition ID: 104006Join a purpose driven winning team, committed to results, in an inclusive and high-performing culture.
Purpose:
The Data Scientist role in the Canadian Banking Analytics is designed for individuals with a curiosity for deriving insights out of data and applying them to address business opportunities, in partnership with global teams and business lines driving innovation and advanced analytics across the Enterprise. The Data Scientist will support key projects, in an agile rapid lab 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 Global teams, business lines, Digital Banking and technology to apply advanced analytics techniques and tools, as well as explore ideas to enhance business opportunities utilizing advanced analytics and artificial intelligence.
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 Functions.
WHATS IN IT FOR YOU?
Opportunity to make an impact in the transformation of Scotiabank
Exposure to global teams and business lines where analytics techniques are being applied
Hands-on practical projects which provide an opportunity to gain new knowledge and develop skills
A compensation program with competitive salary, opportunities for annual performance incentives based on performance thresholds, a competitive benefits program and continuing education programs
COMPETENCIES:
University degree in relevant STEM discipline (Computer Sciences, Electrical/Computer/Software Engineering and Mathematics)
Experience cleaning, transforming and visualizing large data sets working with various data formats (e.g. unstructured logs, XML, JSON, flat files)
Hands-on experience with Big Data ecosystem tools (e.g. Hive, Pig, Sqoop, Spark, Kafka) and experience with NoSQL databases (e.g., Hbase, Cassandra, Druid)
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
Experience with common machine Learning libraries in R, Python, Spark
Experience with UNIX tools and shell scripting
Solid SQL skills for querying relational databases (e.g. SQL Server, DB2, MySQL)
Experience using and implementing visualization tools like PowerBI
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
KEY ACCOUNTABILITES:
Work in an Agile environment to deploy solutions within 90-120 days
Collaborate with business lines and other stakeholders to identify opportunities to drive business value by leveraging Data Science
Ingest massive volumes of structure and unstructured format data, model, transform and store it in a variety of data stores
Leverage distributed computing tools (e.g. Spark, Hadoop) for analysis, data mining and modeling
Collaborate with Data engineering to deploy models and algorithms in production, across business lines and geographies
Create and apply model and algorithm testing strategies to measure conduct multi-variate testing and A/B testing to measure effectiveness of models and make ongoing changes
Prepare detailed documentation to outline data sources, models and algorithms used and developed
Present results to business line stakeholders and help implement real data-driven changes
Lead Research & Development work focused on the effective application of design thinking and scalable advanced techniques to drive ideation and innovation
Collaborate with other Advanced Analytics stakeholders and partners to define data engineering, visualization and machine learning best-practices
Be an integral part of the Advanced Analytics community for incubating ideas and use case acceleration in rapid labs across key markets through advisory, training and scalable solutions
Support analytical use-case delivery, as well as customer/financial benefits tracking and communication
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.