Staff Data Scientist

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

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Job Summary

Job Description

What is the opportunity?

Join the RBC Borealis team, where innovation and data science converge to shape the future of banking! We collaborate with multiple lines of businesses and help them in driving business value and scale by leveraging machine learning, data science and emerging technologies like Generative AI. We are working on some very exciting, cutting-edge problems in Generative AI that will bring in efficiencies in banking processes and create tremendous business impact.

We are seeking a Staff Data Scientist who thrives on thinking outside the box, delves deep into details, and is passionate about exploring innovative approaches in the field of Generative AI and Machine Learning. If you’re ready to contribute to our work and be part of a team that values continuous learning, we want you on board!

What will you do?

  • Work with large amounts of text data – extracting data from documents and various other sources, cleaning, processing and analyzing text data, data preparation for model development and inference

  • Run experiments on Sagemaker, deploy endpoints, perform model inference and training, if required, validate results, and generate reports for specific business use cases

  • Work with open-source large language models, prompting methods and finetuning models for our specific business use cases and work with libraries like huggingface, etc

  • This role involves continuous learning - reading top tier, cutting edge research papers in the field of Generative AI and distilling the knowledge to identify potential applications

  • Collaborate with other data scientists, data engineers, and business stakeholders to deliver high impact projects that will bring efficiency to business processes

What do you need to succeed?

Must Have

  • Prior Programming experience (~5years) in Python is a must – ability to write production level code and documentation

  • Experience working with large datasets – exploring and understanding data, cleaning and pre-processing, performing exploratory data analysis, particularly having prior experience working with large text data is preferred

  • Knowledge of deep learning like transformer-based models and standard machine learning libraries like numpy, pandas, scikit-learn, pytorch data visualization tools and machine learning algorithms like logistic regression, tree-based models, decision trees, random forests, deep learning algorithms

  • Must have experience in Natural Language Processing and Generative AI – text data preparation, vector embeddings, large language models, prompting techniques- few shot, chain-of-thought, etc function calling, hugging face, etc

  • Excellent interpersonal and communication skills (verbal and written), ability to work in a team environment and collaborate effectively with team members, stakeholders, take constructive feedback and iterate

  • Creative, curious and analytical thinker who is self-driven and capable of working in a fast-paced environment, able to deal with ambiguity and offer novel solutions

Nice to Have

  • Have a continuous learning mindset - reading top tier, cutting edge research papers in the field of Generative AI and distilling the knowledge to identify potential applications


  • Experience working with cloud platforms like AWS sagemaker

  • Understanding of vector data basses like chromaDB, pgVector, etc

  • Understanding of knowledge graphs and graph databases like Neo4j

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, to take on progressively greater accountabilities and to building close relationships with clients.

  • Access to a variety of job opportunities across business and geographies.

#LI-Hybrid

#LI-Post

#LI-PK

Job Skills

Artificial Intelligence (AI), Big Data Management, Data Mining, Data Science, Decision Making, Machine Learning, Natural Language Processing (NLP), Predictive Analytics, Python (Programming Language), Statistical Analysis

Additional Job Details

Address:

RBC WATERPARK PLACE, 88 QUEENS QUAY W:TORONTO

City:

TORONTO

Country:

Canada

Work hours/week:

37.5

Employment Type:

Full time

Platform:

TECHNOLOGY AND OPERATIONS

Job Type:

Regular

Pay Type:

Salaried

Posted Date:

2024-10-15

Application Deadline:

2024-11-15

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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We also strive to provide an accessible candidate experience for our prospective employees with different abilities. Please let us know if you need any accommodations during the recruitment process.

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Expand your limits and create a new future together at RBC. Find out how we use our passion and drive to enhance the well-being of our clients and communities at jobs.rbc.com.

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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

Job stats:  5  2  0

Tags: AWS Banking Big Data Data analysis Data management Data Mining Data visualization Deep Learning EDA Generative AI HuggingFace LLMs Machine Learning ML models Model inference Neo4j NLP NumPy Open Source Pandas Prompt engineering Python PyTorch Research SageMaker Scikit-learn Statistics

Perks/benefits: Career development Competitive pay Equity / stock options Flex hours Team events

Region: North America
Country: Canada

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