Job Description

Position Overview

At PNC, our people are our greatest differentiator and competitive advantage in the markets we serve. We are all united in delivering the best experience for our customers. We work together each day to foster an inclusive workplace culture where all of our employees feel respected, valued and have an opportunity to contribute to the company’s success.

As a Data Scientist for PNC's Security Analytics Hub, you will have the opportunity to work fully remote.

This is a remote position that can sit within the PNC footprint, although it may not be available in all jurisdictions. Certain job responsibilities may require in-person, in office activities on a regular basis.

PNC will not sponsor a work visa for this role.

Our team focuses on producing data driven insights into multiple areas of risk facing the bank, including cybersecurity and physical security.

Key Requirements of the Role:
• Strong understanding of advanced data mining techniques, curating, processing, and transforming data to produce sound datasets.
• Strong understanding of the Machine Learning lifecycle - feature engineering, training, validation, scaling, deployment, scoring, monitoring, and feedback loop.
• Experience in Machine Learning including Classification, Forecasting, Anomaly Detection, Pattern Detection, Text Mining, using variety of techniques such as Decision trees, Time Series Analysis, Bagging and Boosting algorithms, Neural Networks, Deep Learning.
• Experience with analytical programming languages, tools, and libraries (Python ecosystem)
• Experience in SQL and relational databases
• Knowledge of Tableau helpful, but not required
• Experience in analyzing complex problems and translating them into an analytical approach.
• Good understanding of coding best practices and building for re-use.
• Strong leadership, stakeholder management, communication, partnership, and teamwork skills.
• Ability to work in an extremely fast paced environment, meet deadlines, and perform at high standards with limited supervision.
• Degree in an analytical field preferred. (e.g., Computer Science, Data Science, Engineering, Applied Mathematics, Data Analysis, Statistics, Operations Research).

Job Description

Leads the implementation of analytical projects that leverage vast amounts of structured and unstructured data to extract actionable business insights.
Directs the data gathering, data processing and data mining of large and complex datasets.
Leads the development of algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
Leads analytical experiments in a methodical manner to find opportunities for product and process optimization. Presents business insights to management using visualization technologies and data storytelling.
Partners with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.

PNC Employees take pride in our reputation and to continue building upon that we expect our employees to be:

Customer Focused - Knowledgeable of the values and practices that align customer needs and satisfaction as primary considerations in all business decisions and able to leverage that information in creating customized customer solutions.
Managing Risk - Assessing and effectively managing all of the risks associated with their business objectives and activities to ensure they adhere to and support PNC's Enterprise Risk Management Framework.

Competencies

Data Architecture – Knowledge and ability to create models and standards to govern which data is collected, and how it is stored, arranged, integrated, and put to use in data systems and in organizations.Data Mining – Knowledge of tools, techniques and practices in data mining technologies used to acquire essential business information.Disruptive Innovation – Knowledge of concepts, principles, and approaches of disruptive innovation; ability to adopt the knowledge into related processes and practices.Information Capture – Knowledge of the processes and the ability to identify, capture and document relevant business information in an auditable, organized, understandable and easily retrievable manner.Machine Learning – Knowledge of principles, technologies and algorithms of machine learning; ability to develop, implement and deliver related systems, products and services.Modeling: Data, Process, Events, Objects – Knowledge of and the ability to use tools and techniques for analyzing and documenting logical relationships among data, processes or events.Prototyping – Knowledge of and ability to implement prototyping disciplines, tools and techniques in evolutionary models within the target environment.Query and Database Access Tools – Knowledge of and the ability to use, support and access facilities for extracting and formatting a database management system.

Work Experience

Roles at this level typically require a university / college degree, with 5+ years of industry-relevant experience. Specific certifications are often required. In lieu of a degree, a comparable combination of education and experience (including military service) may be considered.

Education

Masters