Applied Data Scientist

Old National Bank•Evansville, IN

About The Position

Old National Bank is seeking a skilled and innovative Applied Data Scientist to join its team within Corporate Treasury. The role uses econometrics, advanced analytics, and machine learning to analyze large datasets, uncover insights, and inform strategic decisions. It supports the bank’s data-driven efforts to improve customer experience, risk management, and operational efficiency.

Requirements

Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, or a related field.
Proven experience as a Data Scientist; experience in financial services is preferred.
Proficiency in programming languages such as SAS, Python, R, or SQL.
Strong knowledge of machine learning techniques, statistical modeling, and data mining.
Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
Strong analytical and problem-solving skills, including the ability to work with large, complex datasets.
Strong communication skills and the ability to present complex information clearly and concisely to technical and non-technical stakeholders.
Ability to work collaboratively in a team environment and manage multiple projects simultaneously.

Nice To Haves

Knowledge of banking regulations and compliance.

Responsibilities

Analyze and interpret complex datasets to identify patterns, trends, and insights that can drive business decisions.
Develop and implement predictive models and algorithms to support banking functions, including behavioral analysis related to loan and deposit performance metrics.
Collaborate with cross-functional teams, including IT, marketing, and risk management, to define data requirements and deliver actionable insights.
Communicate findings and recommendations to stakeholders through clear, concise reports and visualizations.
Stay current with advancements in data science, machine learning, and artificial intelligence, and apply them to improve analytical methodologies.
Ensure data integrity and quality by developing and maintaining robust data pipelines.
Provide guidance and mentorship to junior data scientists and analysts.