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Senior Data Scientist - Halifax

RBC

Halifax

On-site

CAD 70,000 - 90,000

Full time

Today
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Job summary

A leading financial institution in Halifax is seeking a Data Scientist to design and implement machine learning solutions. You will work with a team of data scientists to analyze large datasets and collaborate with business partners to extract actionable insights. Candidates should have a Bachelor’s degree in a quantitative field and 1-2 years of experience in delivering data-driven solutions. This role offers varied responsibilities and opportunities for professional growth within a dynamic team.

Benefits

Comprehensive Total Rewards Program
Competitive compensation
Flexible work/life balance options
World-class training program in financial services

Qualifications

  • 1-2 years of experience delivering data-driven solutions using machine learning, AI, predictive analytics, and/or statistical modeling.
  • Familiar with popular programming languages, libraries, and frameworks for data science (Python, SQL, pandas, numpy, sklearn).
  • Experience in data visualization and communicating technical concepts to a non-technical audience.

Responsibilities

  • Support the development and deployment of statistical / AI / ML solutions.
  • Collect, transform, and analyze large datasets to extract insights.
  • Collaborate with business partners to produce insights from business-defined requirements.

Skills

Python (Programming Language)
Machine Learning (ML)
Data Science
Predictive Analytics
Data Mining
Actuarial Modeling
Natural Language Processing (NLP)
Big Data Management
Commercial Acumen
Decision Making

Education

Bachelor’s in Computer Science or related field
Master’s or Ph.D. in a quantitative field
Job description
Job Description
What is the opportunity?

In this role, you will design and implement data science/machine learning solutions using RBC’s enterprise suite of AI and analytics tools. The group specializes 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, the group applies generative AI, machine learning, and statistical modelling techniques to help RBC improve data controls, understand the changing business environment, discover new growth opportunities, and determine where improvements can be made.

What will you do?
  • Support the development and deployment of statistical / AI / ML solutions, working in a team of data scientists and data engineers.
  • Collect, transform, and analyze large datasets (structured and unstructured) to extract insights, support model development, and enable predictive analytics.
  • Validate, measure, and document model performance in accordance with business and stakeholder requirements.
  • Collaborate with business partners to produce insights from business-defined requirements and hypotheses.
  • Leverage visualization tools/packages to story-tell and to convey data-driven insights with actionable recommendations to business partners and key stakeholders.
  • Quickly learn new methods, tools, and technologies.
What do you need to succeed?
Must Have:
  • Bachelor’s in Computer Science, Engineering, Statistics, Mathematics, or a related quantitative field.
  • 1-2 years of experience delivering data-driven solutions using machine learning, AI, predictive analytics, and/or statistical modeling.
  • Familiar with popular programming languages, libraries, and frameworks for data science (Python, SQL, pandas, numpy, sklearn).
  • Experience in data visualization and communicating technical concepts to a non-technical audience.
  • Excellent problem solving, collaboration, and organizational skills.
Nice to have:
  • Master’s or Ph.D. in a quantitative field.
  • Experience with data extract, transform, and load processes on a variety of data types.
  • Experience with generative AI, deep learning frameworks (PyTorch, TensorFlow), vector databases, and/or graph data.
  • Knowledge of lifecycle of data science products from design to delivery.
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
Job Skills

Actuarial Modeling, Big Data Management, Commercial Acumen, Data Mining, Data Science, Decision Making, Machine Learning (ML), Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language)

Additional Job Details

Address: 175 WESTERN PKY:BEDFORD

City: Bedford

Country: Canada

Work hours/week: 37.5

Employment Type: Full time

Platform: CHIEF LEGAL & ADMIN OFFICE GRP

Job Type: Regular

Pay Type: Salaried

Posted Date: 2025-12-19

Application Deadline: 2026-02-21

Note: Applications will be accepted until 11:59 PM on the day prior to the application deadline date above

Inclusion and Equal Opportunity Employment

At RBC, we believe an inclusive workplace that has diverse perspectives is core to our continued growth as one of the largest and most successful banks in the world. Maintaining a workplace where our employees feel supported to perform at their best, effectively collaborate, drive innovation, and grow professionally helps to bring our Purpose to life and create value for our clients and communities. RBC strives to deliver this through policies and programs intended to foster a workplace based on respect, belonging and opportunity for all.

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