Senior Data Scientist - Pittsburgh, PA

Position Title: Senior Data Scientist

Business Unit: Strategy and Innovation

Reports to: Manager of Data Science

Position Overview:

This position leads the development and deployment of advanced analytics and machine learning solutions across fraud detection, document intelligence, customer analytics, and treasury forecasting. The Senior Data Scientist partners with business leaders to translate complex financial and operational problems into scalable models and AI solutions, with a focus on production deployment, model governance, and measurable business impact.

Primary Responsibilities:

Lead the design and development of machine learning models across use cases such as fraud detection, customer behavior modeling, document intelligence (OCR/Doc AI), and financial forecasting.

Partner with senior leadership and stakeholders to identify opportunities, define analytical approaches, and translate business needs into data-driven solutions.

Architect and oversee end-to-end production ML systems, including data pipelines, feature stores, model deployment, and monitoring of model performance and drift.

Provide technical leadership, mentorship, and guidance to junior and mid-level data scientists; review work to ensure quality, accuracy, and best practices.

Communicate complex analytical findings to both technical and non-technical audiences; influence decision-making through clear storytelling and recommendations.

Establish and maintain best practices in modeling, documentation, model governance, and performance monitoring to ensure scalability and compliance.

Design and evaluate experiments (e.g., A/B testing, back testing) to measure model impact on business outcomes such as fraud loss reduction, customer retention, and revenue growth.

Drive innovation by researching and applying new tools, techniques, and methodologies in data science and analytics.

Collaborate cross-functionally with data engineering, IT, and business teams to ensure alignment and successful implementation of solutions.

Design and implement NLP, computer vision, and hybrid rule-based/ML systems for document extraction, classification, and text analytics use cases.

Performs other related duties and projects as assigned.

All employees have the responsibility and the accountability to serve as risk managers for their businesses by understanding, reporting, responding to, managing and monitoring the risk they encounter daily as required by F.N.B. Corporation’s risk management program.

F.N.B. Corporation is committed to achieving superior levels of compliance by adhering to regulatory laws and guidelines.   Compliance with regulatory laws and company procedures is a required component of all position descriptions. 

BA or BS

5

Excellent communication skills, both written and verbal    

Excellent organizational, analytical and interpersonal skills    

Detail-oriented    

Excellent project management skills    

MS Excel - Intermediate Level    

MS PowerPoint - Intermediate Level    

Ability to use a personal computer and job-related software    

Excellent management skills    

Python (pandas, scikit-learn, etc.)

SQL (advanced querying, data extraction)

Machine Learning (supervised/unsupervised)

Statistical modeling & experimentation

Data Wrangling & Feature Engineering

N/A   

N/A    

It is the policy of F.N.B. Corporation (FNB) and its affiliates not to discriminate against any employee or applicant for employment because of age, race, color, religion, sex, national origin, disability, veteran status or any other category protected by law. It is also the policy of FNB and its affiliates to employ and advance in employment all persons regardless of their status as individuals with disabilities or veterans, and to base all employment decisions only on valid job requirements. FNB provides all applicants and employees a discrimination and harassment free workplace.

FNB will not provide sponsorship for employment-based visas for this position; only candidates who are legally authorized to work in the U.S. will be considered.