OverviewOld National Bank is seeking a skilled and innovative Applied Data Scientist to join our dynamic team within Corporate Treasury. The Applied Data Scientist will leverage econometrics, advanced analytics and machine learning techniques to analyze large datasets, uncover insights, and drive strategic decisions. This role is crucial in enhancing our data-driven approach to improving customer experience, risk management, and operational efficiency.
Salary Range
The salary range for this position is $79,400/yr - $156,000/yr plus bonus. The base salary indicated for this position reflects the compensation range applicable to all levels of the role across the United States. Actual salary offers within this range may vary based on a number of factors, including the specific responsibilities of the position, the candidate’s relevant skills and professional experience, educational qualifications, and geographic location.
Key Accountabilities
- Analyze and interpret complex data sets to identify patterns, trends, and insights that can drive business decisions.
- Develop and implement predictive models and algorithms to support various 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 these advancements 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.
Qualifications and Education Requirements
- Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science or related field.
- Proven experience as a Data Scientist, preferably within the financial services industry.
- 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, with the ability to work with large, complex datasets.
- Strong communication skills, with the ability to present complex information clearly and concisely to both technical and non-technical stakeholders.
- Knowledge of banking regulations and compliance is a plus.
- Ability to work collaboratively in a team environment and manage multiple projects simultaneously.
