Data Scientist Senior - People Analytics & Quantitative Insights

PNC Bank•Pittsburgh, PA

2d•Onsite

About The Position

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 Senior within PNC's Human Resources organization, you will be based in Pittsburgh, PA. Responsibilities include, but are not limited to: Partner with business stakeholders to identify analytical opportunities, applying quantitative methods and statistical reasoning to interpret workforce data and develop data-driven solutions that inform strategic and operational decision making. Utilize statistical analysis, data modeling, and data visualization techniques to design and deliver analyses and dashboards that quantify relationships between HR metrics and business outcomes. Manage and prioritize multiple analytical initiatives, balancing complex data requests, evolving business needs, and competing deadlines in a fast-paced environment. Analyze large, complex datasets and model outputs using tools such as SAS, Python, or R, translating results into actionable insights and recommendations, and communicating findings effectively to both technical and non-technical audiences. PNC is an in-office company that fosters a supportive culture where employees can thrive and achieve balance. We encourage candidates to connect with their recruiter and hiring manager to understand workplace expectations and ensure the role aligns with their goals. PNC will not provide sponsorship for employment visas or participate in STEM OPT for this position. 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.

Requirements

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, job specific certification(s), and experience (including military service) may be considered.

Nice To Haves

Analytical Thinking
Competitive Advantages
Data Analytics
Data Mining
Data Science
Machine Learning (ML)
Data Architecture
Data Mining
Disruptive Innovation
Information Capture
Machine Learning
Modeling: Data, Process, Events, Objects
Prototyping
Query and Database Access Tools

Responsibilities

Partner with business stakeholders to identify analytical opportunities, applying quantitative methods and statistical reasoning to interpret workforce data and develop data-driven solutions that inform strategic and operational decision making.
Utilize statistical analysis, data modeling, and data visualization techniques to design and deliver analyses and dashboards that quantify relationships between HR metrics and business outcomes.
Manage and prioritize multiple analytical initiatives, balancing complex data requests, evolving business needs, and competing deadlines in a fast-paced environment.
Analyze large, complex datasets and model outputs using tools such as SAS, Python, or R, translating results into actionable insights and recommendations, and communicating findings effectively to both technical and non-technical audiences.
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.

Benefits

medical/prescription drug coverage (with a Health Savings Account feature)
dental and vision options
employee and spouse/child life insurance
short and long-term disability protection
401(k) with PNC match
pension and stock purchase plans
dependent care reimbursement account
back-up child/elder care
adoption, surrogacy, and doula reimbursement
educational assistance, including select programs fully paid
a robust wellness program with financial incentives
maternity and/or parental leave
up to 11 paid holidays each year
9 occasional absence days each year, unless otherwise required by law
between 15 to 25 vacation days each year, depending on career level; and years of service.