Senior Data Scientist - Pittsburgh, PA at First National Bank Of Pennsylvania

## Primary Office Location:

**Please note: this on-site position is based at our Financial Center in Pittsburgh, PA. Candidates must be local or willing to relocate to the area.

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.**

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.

BA or BS

5

Detail-oriented

Excellent project management skills

MS Excel - Intermediate Level

MS PowerPoint - Intermediate Level

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

Equal Employment Opportunity (EEO):