Data Scientist - Toronto, Canada - Royal Bank of Canada

Royal Bank of Canada

Verified Company

Toronto, Canada

1 week ago

Posted by:

Sophia Lee

beBee Recruiter

Description

Come Work with Us
At RBC, our culture is deeply supportive and rich in opportunity and reward. You will help our clients thrive and our communities prosper, empowered by a spirit of shared purpose.

Whether you're helping clients find new opportunities, developing new technology, or providing expert advice to internal partners, you will be doing work that matters in the world, in an environment built on teamwork, service, responsibility, diversity, and integrity.

Job Title
Data Scientist - Alternative Data and AI

WHAT IS THE OPPORTUNITY?

WHAT WILL YOU DO?

Design and develop AI ML models for deriving insights from Alternative data structured and unstructured
Experienced with building front to back AIML models with MLOps integration and active learning on the cloud
Highly Proficient in statistical functions and distributions
Highly Proficient in AIML algorithms and techniques like Exploratory data analysis, Feature Engineering, Model selection, Hyper Parameter tuning etc.
Experience with Linear Programming, Quadratic Programming etc.
Build anomaly detection model leveraging packages like Prophet or similar
Build anomaly detection models for geospatial and other practices based on domain requirements.
Experience with techniques like transfer learning, K shot and no shot learning

WHAT DO YOU NEED TO SUCCEED?

Must have:

Selfstarter and delivery oriented experienced Data Scientist
Experience working with alternative data
Experience with Cloud, Distributed computing and Data Science
Excellent communication and presentation skills. Proven ability to connect with internal and external stakeholders and excel in a fastpaced environment.
Expertise in time series modeling (ARIMA, Prophet etc.)
Expertise in statistical functions, distance functions and distribution analysis (E.g. Dynamic Time Warping, Earth Movers Distribution etc. )

Nice-to-have:

2+ years of financial industry experience
2+ years of AI and Big Data Analytics Experience
Experience with and exploratory analysis of alternative data for financial use cases.
Experience with one or more cloud platforms (Azure, AWS or GCP)
Experience with orchestration frameworks like Airflow or Azure data factory
Experience with distributed notebook environments like Databricks
Experience building AI driven Data Quality frameworks and other data governance tools and capabilities
Experience building meta data driven AI and statistical models for repeatable insight generation
Experience with Model deployment, Model validation, Model assessment, Model Monitoring etc.

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 highperforming team
A worldclass training program in financial services
Flexible work/life balance options
Opportunities to do challenging work

Job Summary

Address:

TORONTO, Ontario, Canada

City:

CAN-ON-TORONTO, USA-NJ-JERSEY CITY

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

Capital Markets

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

Application Deadline:

Inclusion
and Equal Opportunity Employment
At RBC, we embrace diversity and inclusion for innovation and growth.

We are committed to building inclusive teams and an equitable workplace for our employees to bring their true selves to work.

We are taking actions to tackle issues of inequity and systemic bias to support our diverse talent, clients and communities.

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