US Wealth Management Data Scientist, RBC Capital Markets, LLC, Minneapolis, MN:

Job Description Analyze, design and implement data science / machine learning ("ML") solutions using RBC's enterprise suite of analytics tools. Reviewing large data sets to explore and discover new insights that would have not been possible with traditional analytics. Leveraging leading edge technologies and capabilities, this role applies machine learning and statistical modelling techniques to help RBC US Wealth Management understand the changing business environment, discover new growth opportunities and determine where business improvements can be made. The role will 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 and transform data (structured/non-structured). Develop and deploy ML solutions at scale. Prepare, integrate large and varied datasets and implement statistical and ML models using Python and R. 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.

Telecommuting permitted up to 2 days per week.

Full time employment, Monday - Friday, 40 hours per week. Salary:

$142,230

per year.

Minimum Requirements Must have a Bachelor's degree or foreign equivalent in Statistics, Mathematics, Computer Science, or related field and 5 years of progressive post-baccalaureate related work experience.

Alternatively, the employer will accept a Master's degree or foreign equivalent in Statistics, Mathematics, Computer Science, or related field and 3 years of related work experience.

Working in the wealth management industry, with the ability to develop analyses and models relevant for financial advisors and senior management;

Creating automated Data ETL processes using scripting Languages, such as Python/SQL, to consolidate data from multiple sources and to streamline future development;

Creating data features for machine learning;

Automating and documenting data analysis processes using Python, including effectively transitioning completed work to a production support team, optimizing workflow and enabling the allocation of resources to additional projects;

Transforming and analyzing large data sets, including historical transactional data, to develop insights and effectively identify anomalies;

Design, development, and implementation experience utilizing data science projects using scripting languages (Python, Java, R, and SQL);

Ability to code, explain, and select intermediate machine learning models (Random Forest, XGBoost, and K-means); and

Increasing adoption of models by educating business users on the modeling process and the reliability of models.

Employer will accept any suitable combination of education, training, or experience.

RBC's compensation philosophy and principles recognize the importance of a highly qualified global workforce and plays a critical role in attracting, engaging and retaining talent that:

Drives RBC's high-performance culture

Enables collective achievement of our strategic goals

Generates sustainable shareholder returns and above market shareholder value

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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