Applied Data Scientist

Old National Bank•Evansville, IN

5d•$79,400 - $156,000

About The Position

Old National Bank is seeking a skilled and innovative Applied Data Scientist to join its Corporate Treasury team. The role uses econometrics, advanced analytics, and machine learning to analyze large datasets, uncover insights, and inform strategic decisions that improve customer experience, risk management, and operational efficiency. The position collaborates across teams and provides guidance to junior data scientists and analysts.

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.
Excellent analytical and problem-solving skills, including the ability to work with large, complex datasets.
Strong communication skills and ability to present complex information clearly to technical and non-technical stakeholders.
Ability to work collaboratively in a team environment and manage multiple projects simultaneously.

Nice To Haves

Experience as a Data Scientist in the financial services industry.
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 for banking functions, including behavioral analysis related to loan and deposit performance metrics.
Collaborate with IT, marketing, risk management, and other cross-functional teams 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.