Senior Full Stack Data Scientist

What is the Opportunity?

The Liquidity Analytics and Funds Transfer Pricing (FTP) - Global Markets team within RBC Corporate Treasury is at the forefront of enterprise liquidity research, designing prescriptive risk treatments that enable the Bank to optimize liquidity and funding risk exposures. Our work ensures resilience under both normal and stressed market conditions while aligning funding costs with business activities through FTP. We leverage cutting-edge analytics, machine learning, artificial intelligence (AI), generative AI and automation to deliver actionable insights to senior leadership and front-office business partners.

Are you analytically curious, a continuous learner who is an out-of-the-box thinker and a self-starter? If so, you may be the right fit for our Team.

We are seeking a Full Stack Data Scientist with a passion for advanced analytics, liquidity risk, and financial modeling. You will lead the development of scalable analytics solutions, integrating data science, machine learning, AI, generative AI, and automation to enhance liquidity risk management, FTP methodologies and advisory to the Capital Markets businesses. This high-impact role involves collaboration across Treasury, Capital Markets, Finance, Group Risk Management, and Technology teams to modernize analytics and improve decision-making.

What will you do?

• Design and implement full-stack data solutions to support liquidity analytics, integrating Python-based machine learning models with cloud-based data pipelines.

• Optimize data infrastructure by developing scalable ETL pipelines, APIs, and analytics dashboards to enhance decision-making.

• Leverage AI/ML techniques for liquidity forecasting, stress testing, and pricing optimization to improve risk management strategies.

• Automate liquidity and FTP analytics by integrating predictive analytics, NLP, and statistical models to drive efficiency and accuracy.

• Develop interactive visualization tools (e.g., Power BI, Tableau, etc.) to translate complex liquidity risk concepts into actionable insights for stakeholders.

• Provide data-driven insights and guidance to business partners, ensuring transparency in FTP methodologies and promoting margin stability.

What do you need to succeed?

Must have:

• Experience with Retrieval-Augmented Generation (RAG): Including integration with vector databases, embedding techniques, and search optimization.

• Unstructured Data Expertise: Proven ability to handle unstructured data (e.g., text, audio) and process large-scale textual datasets from financial reports, news sources, and other data streams.

• Generative AI and LLMs: Expertise in deep-learning-driven generative models, including large language models (LLMs) and advanced natural language processing (NLP) techniques.

• Model Fine-Tuning and Deployment: Hands-on experience in fine-tuning and deploying deep learning models, with a focus on performance optimization.

• MLOps Frameworks: Practical knowledge of MLOps frameworks and best practices for continuous integration, deployment, and monitoring of ML models.

• Speech-to-Text Technologies: Experience with technologies like Whisper and familiarity with cutting-edge text generation models like GPT-4 and Llama.

• Big Data Technologies: Strong background in big data tools, including Spark, Kafka, and optimizing queries in relational databases such as Postgres.

• Fast-Paced Environments: Background in working within fast-paced environments, particularly in fintech, AI research, or startup ecosystems.

• Distributed Computing: Understanding of distributed computing principles and client-server architecture, enabling scalable deployment of ML models and inference pipelines.

• Education: Master's or Ph.D. in a relevant quantitative field (e.g., Data Science, AI, Machine Learning, Computer Science, Statistics, Mathematics, Engineering, Finance, Economics, or Quantitative Finance).

• Experience: 5+ years of experience in data science, machine learning, and data engineering.

• Technical Skills:

  • Strong programming skills in Python and SQL.

  • Experience with big data tools (e.g., Databricks, Snowflake, Spark, Hadoop).

  • Cloud computing expertise (e.g., AWS, Azure, GCP) for ML and data infrastructure.

  • Deep understanding of ML/AI algorithms (e.g., supervised/unsupervised learning, deep learning, NLP, graph analytics).

  • Proficiency in MLOps (model deployment, versioning, CI/CD).

  • Experience with chatbot development (UI/UX).

  • Experience with LLMs (Large Language Models) and Generative AI.

  • Hands-on experience with Reinforcement Learning.

• Business Acumen: Ability to align data science initiatives with business goals.

• Communication Skills: Strong ability to bridge technical and non-technical stakeholders.

Nice-to-Have Skills

• Treasury and capital markets

• Experience with financial modeling, risk analytics, or fintech applications.

• Professional certifications (CFA, FRM, AWS/GCP/Azure).

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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Additional Job Details

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