Senior data scientist – GCS

Royal Bank of Canada (RBC)’s Technology and Operations Department based in Toronto, ON is inviting applications from suitable candidates for the position of Senior data scientist. RBC’s Technology and Operations Department focuses on enhancing the bank’s technological infrastructure and operational efficiency. It provides innovative tech solutions and operational support to streamline processes and bolster cybersecurity. The department is integral to RBC’s ability to deliver reliable and secure financial services. Its role is pivotal in maintaining RBC’s competitive edge in the banking sector. It ensures seamless and efficient banking operations. The candidates selected for the vacancy will be required to start the work as soon as possible.

Also hiring: Administrative assistant

Job Description:

Employer Name: Royal Bank of Canada (RBC)
Department: Technology and Operations
Position: Senior data scientist – GCS
No of Vacancies: 2
Salary: Salary is not mentioned, $65.00 – $70.00 hourly estimated salary
Employment Type: Full time/Regular
Job Category: Technology
Location: Toronto, ON, Canada
Shift: 37.5 Hours/Week
Requisition ID: R-0000094497

Requirements:

Languages: Candidates must have knowledge of the English Language
Education: Candidates should have completion of PhD in a quantitative field Engineering, Statistics, Mathematics, Computer Science, Economics, Sociology and Psychology
Experience: Candidates should have Previous experience in cybersecurity and fraud domains

Physical Requirements:

  • The candidates should demonstrate a strong data sense, critical thinking, and technical documentation skills

Other Requirements:

  • The candidates should have a undergraduate degree or master degree and advanced programming skills (Python, PySpark) and experience in developing machine learning models using supervised and unsupervised approaches
  • The candidates should have experience with data preprocessing, feature and representation learning, and anomaly or outlier detection
  • The candidates should have a passion for simplifying and automating work, making things better, continuous learning, solving open-ended problems, improving efficiency, and helping others
  • The candidates should have strong communication skills with the ability to work cross-functionally to articulate, measure, and solve issues and experience with graph analytics
  • The candidates should have experience with MLOps to build end-to-end pipelines and deploy models in production
  • The candidates should have expertise in Big Data, possess strong Communication skills and proficient in Data Analysis and a solid foundation in Data Science
  • The candidates should be knowledgeable in Deep Learning, excel in Machine Learning and experience in Natural Language Processing (NLP)
  • The candidates should be skilled in Predictive Analytics, proficient in PySpark and advanced programming skills in Python
  • The candidates should have experience with Supervised Learning and experience with Unsupervised Learning

Responsibilities:

  • The candidates should be able to 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
  • The candidates should be able to design and implement end-to-end data pipelines: from data cleaning to model development to writing production-level code
  • The candidates should be able to implement supervised and unsupervised machine learning models, data mining methods, statistical analysis, and pipelines to prepare and integrate various data types and sources
  • The candidates should be able to quickly learn new methods, big data tools, and technologies presented in research communities to implement and adapt within our data products and models
  • The candidates should be able to collaborate proactively with various business and operation units to design innovative solutions to optimize processes and deploy production-scale solutions
  • The candidates should be able to work on challenging and research-based initiatives using advanced machine learning methods focusing on tangible outcomes

Benefits:

  • The candidates will get bonuses, flexible benefits, competitive compensation, commissions, and stock

How to apply:

If the position is fit for you and the basic requirements are fulfilled then you can now apply directly to the employer (along with your resume) through the below-mentioned details.

Apply Online

 

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