Senior Data Scientist - GCS (rbc)

Job Description

What is the opportunity?

We have an exciting opportunity in Global Cyber Security!

As a Senior Data Scientist on our team, you will design and implement machine learning products to detect digital and cyber threats. You will provide valuable insights to our business stakeholders to protect RBC clients and data. 

Data Science allows us to identify trends, anticipate malicious behaviours, perform pattern matching, discover new threats, and predict the outcomes of future events.  Working as part of the Joint Security Operations Center (JSOC), you’ll specialize in taking full advantage of large data sets to explore and discover new insights that would have not been possible with traditional analytics. Leveraging leading edge technologies and capabilities, you will apply machine learning and statistical modelling techniques to help RBC to proactively defend its digital information. 

What will you do?

• Work closely with stakeholders to understand their needs and build solutions using advanced machine learning methods in the domains of fraud, cybersecurity, and data privacy

• Design and implement end-to-end data pipelines: from data cleaning to model development to writing production level code

• Implement supervised and unsupervised machine learning models, data mining methods, statistical analysis, and pipelines to prepare and integrate various data types and sources

• Quickly learn new methods, big data tools and technologies presented in research communities to implement and adapt within our data products and models

• Collaborate proactively with various business and operation units to design innovative solutions to optimize processes and deploy production-scale solutions

• Work on challenging and research-based initiatives using advanced machine learning methods focusing on tangible outcomes

What do you need to succeed?

Must have:

• At least an undergraduate degree (PhD. or Masters preferred) in a quantitative field (Engineering, Statistics, Mathematics, Computer Science, Economics, Sociology, Psychology etc.)

• Advanced programming skills (python, pyspark) and experience in developing machine learning models using supervised and unsupervised approaches; experience with data preprocessing, feature and representation learning, anomaly/outlier detection

• Strong data sense, critical thinking, and technical documentation skills

• A passion for simplifying and automating work, making things better, continuous learning, solving open-ended problems, improving efficiency, and helping others

• Strong communication skills with ability to work cross-functionally to articulate, measure and solve issues

Nice-to-have:

• Previous experience in cybersecurity/fraud domains

• Experience with MLOps to build end-to-end pipeline and deploying models in production

• Experience with graph analytics

What’s in it for you?

We thrive on the challenge to be our best, progressive thinking to keep growing, and working together to deliver trusted advice to help our clients thrive and communities prosper. We care about each other, reaching our potential, making a difference to our communities, and achieving success that is mutual.

• A comprehensive Total Rewards Program including bonuses and flexible benefits, competitive compensation, commissions, and stock where applicable

• Leaders who support your development through coaching and managing opportunities

• Ability to make a difference and lasting impact

• Work in a dynamic, collaborative, progressive, and high-performing team

• A world-class training program in financial services

• Flexible work/life balance options

• Opportunities to do challenging work

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Job Skills

Big Data, Communication, Data Analysis, Data Science, Deep Learning, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, PySpark, Python (Programming Language), Supervised Learning, Unsupervised Learning

Additional Job Details

330 FRONT ST W:TORONTOTORONTOCanada37.5Full timeTECHNOLOGY AND OPERATIONSRegularSalaried2024-07-262024-09-13