below marketmost similar roles pay hereabove market
This role pays less than
75%
of similar roles. Most pay
$129,032–$214,000
— the blue band above.
At the midpoint, this role pays about
$129k
versus about
$172k
for comparable roles.
Based on 240 similar postings.
Employer
About PNC
PNC is one of the largest diversified financial services institutions in the U.S., based in Pittsburgh, PA, it provides retail banking, corporate banking, and asset management.
PNC currently has
159 open roles
on FindRole.
Listed pay typically runs
$91,000–$179,200
across 22 roles with salary data.
As a Data Scientist within the Anti-Money Laundering Analytics & Modeling organization, you will join a cohesive team utilizing statistical techniques to build models that detect, monitor, and avert concerning patterns of account activity. You will identify risk indicators within customer, account, and transaction datasets to develop innovative, potentially patentable AML projects. Your daily responsibilities include data set creation, analysis, reporting, model building, monitoring, and documentation. You will use machine learning algorithms such as logistic regression, clustering, gradient boosting, and neural networks. Required technical skills include proficiency in Python, PySpark, R, and SQL, along with expertise in experimental design and probability theory. You will solve complex business problems by extracting actionable insights from structured and unstructured data to optimize products and processes within a banking context.
What does a Data Scientist earn?
Median $173200 from 338 postings across 66 companies.
Build statistical models using machine learning algorithms like logistic regression, clustering, and neural networks to detect suspicious account activity.
Extract usable information from large datasets including customer, account, and transactional data.
Identify risk indicators and patterns within firm datasets to develop new anti-money laundering strategies.
Perform data gathering, processing, and mining for large and complex datasets.
Monitor and document model performance to ensure accuracy and compliance.
Communicate complex analytical results and technical concepts to senior executives and non-technical stakeholders.
Run methodical analytical experiments to find opportunities for product and process optimization.
Partner with data engineers and architects to develop data-driven solutions for the business.
What we're looking for
Roles at this level typically require a university/college degree.
3+ years of relevant or direct industry experience are typically required.
Master's degree or higher in a quantitative field (preferred).
Experience with data mining and data preparation for ML models (preferred).
Proficiency in statistical methods including experimental design, probability theory, and sampling (preferred).
Expertise in building, scaling, and optimizing machine learning systems with industry recognized frameworks (preferred).
Strong programming skills in Python, PySpark, R, and/or SQL (preferred).
Experience in banking, financial services, anti-fraud, or anti-money laundering modeling (preferred).