Data Scientist (Applied AI)

About the role

As a Data Scientist you will problem solve, analyze, design, implement and monitor machine learning applications using state-of-the-art tools and algorithms. As part of the US Wealth Management Applied AI team, your day-to-day work will include many exciting fields in applied statistics and machine learning, including causal inference and experimentation, time-series forecasting, predictive marketing and advertising, and model interpretation.

Responsibilities

• Collaborate with key business partners and stakeholders to understand business objectives/opportunities and problem statements in order to provide solutions that align to business needs that are actionable with a tangible outcome.
• Prepare, analyze, and transform data from structured and unstructured sources.
• Develop, implement, and deploy statistical and ML models at scale.
• Leverage visualization tools/packages to story-tell and to convey data-driven insights with actionable recommendations to key stakeholders.
• Quickly learn new methods, tools and technologies presented in research communities to implement, adapt and innovate.
• Effectively communicate findings to business partners and executives.
• Develop predictive data models, quantitative analyses and visualization of targeted, big data sources.
• Assist Senior Data Scientists throughout the ML lifecycle.
• Perform offline model evaluation and validation.
• Build dashboards and communicate insights.
• Monitor production models for drift and performance.
• Document experiments and support AI governance.
• Present findings to technical and business stakeholders.

Requirements

• Master’s or PhD in Computer Science, Statistics, Mathematics, or Physics.
• 2-3 years of experience in data solutions and applying data techniques.
• Strong knowledge of design, development, and implementation experience utilizing data science technologies.
• 3+ years of experience in machine learning, predictive analytics, and statistical modeling.
• Experience with causal inference and experimentation, time-series forecasting, predictive marketing and advertising, and model interpretation.
• Experience with libraries such as:
  • ML/DL: sklearn, tensorflow, pytorch
  • Analysis: pandas, pySpark, scala Spark, SQL, Hive
• Excellent analytical, problem solving, time management and organizational skills.
• Experience delivering presentations to wide audiences, both technical and non-technical.
• Basic understanding of Generative AI and LLMs.
• Familiarity with RAG concepts.
• Experience using OpenAI, Claude, Gemini, or Azure OpenAI APIs.
• Understanding of prompt engineering.
• Ability to evaluate LLM outputs.
• Awareness of hallucinations and responsible AI.

Nice-to-have

• Good understanding of AWS Big Data services such as Amazon S3, EMR and Glue; and ML capabilities including Sagemaker.
• Experienced with Jupyter Notebooks, IntelliJ, Visual Studio Code or other notebook environments.
• Experience with visualization tools such as Tableau, QuickSight, Looker.
• Experience working in Unix/Linux environments.
• Experience working as part of an agile team using Github and JIRA.
• Experience with digital data collection tools such as Google Analytics.
• Exposure to Snowflake, Databricks, Sparr, Power BI or Tableau.
• MLflow, NLP, embeddings, semantic search.
• Feature stores and model monitoring.
• REST APIs and FastAPI.

Benefits

• A comprehensive Total Rewards Program including competitive compensation and flexible benefits, such as 401(k) program with company-matching contributions, health, dental, vision, life, disability insurance, and paid-time off.
• 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.
• Opportunities to do challenging work.
• Opportunities to build close relationships with clients.

Pay

The expected salary range for this position is $80,000-$140,000 depending on your experience, skills, and registration status, market conditions and business needs. You have the potential to earn more through RBC’s discretionary variable compensation program which gives you an opportunity to increase your total compensation, provided the business meets its performance targets and you meet your individual goals.

Location: Minneapolis, MN (250 Nicollet Mall)
Employment Type: Full time
Work hours/week: 40