Data Scientist - Retail Banking (ML & Predictive Modeling)
About The Position
We are seeking a highly analytical and technically skilled Data Scientist to support the development, evaluation, implementation, and optimization of advanced predictive models within Retail Banking. This role will focus on building machine learning and statistical models, designing and analyzing experiments, enhancing data-driven business strategies, and communicating actionable insights to business leaders and executive stakeholders. The ideal candidate combines strong predictive modeling expertise with hands-on experience working with large-scale data environments and modern programming languages. This position offers the opportunity to expand existing production modeling frameworks while partnering closely with risk, strategy, analytics, and business teams.
Requirements
- Bachelor's Degree in Statistics, Mathematics, Data Science, Computer Science, Economics, Finance, Engineering, or a related quantitative field.
- 2-3 years of professional experience in data science, predictive analytics, statistical modeling, machine learning, or quantitative analysis.
- Experience developing and implementing predictive models using large datasets.
- Strong understanding of statistical modeling, machine learning techniques, and model performance evaluation.
- Experience building and validating credit risk, retail banking, or customer analytics models.
- Proficiency in one or more of the following programming languages: Python, R, or SAS
- Experience with: PySpark, R Shiny, or SQL
- Experience working with large-scale data environments and big data technologies, including Teradata, Hadoop, AWS, Impala, Hive, or Trino
- Experience with relational database platforms such as: Oracle, MySQL, PostgreSQL, TOAD
- Experience using GitHub or other version control platforms.
- Strong communication and presentation skills with the ability to translate technical findings for non-technical audiences.
Nice To Haves
- Master's Degree in a quantitative discipline.
- Experience supporting Retail Banking, Consumer Banking, Risk Management, Credit Risk, or other Financial Services functions.
- Experience with model governance, model risk management, and regulatory expectations within the banking industry.
- Prior experience supporting EAD, PD, LGD, CECL, stress testing, or other risk modeling frameworks.
- Knowledge of model deployment, model monitoring, and production support processes.
- Experience working in Agile or cross-functional analytics environments.
- Demonstrated ability to influence business decisions through advanced analytics and data storytelling.
- Experience presenting analytical results to senior leadership and executive stakeholders.
Responsibilities
- Performs analytical tasks on vast amounts of structured and unstructured data to extract actionable business insights.
- Participates in the data gathering, data processing and data mining of large and complex datasets.
- Develops algorithms using advanced mathematical and statistical techniques like machine learning to predict business outcomes and recommend optimal actions to management.
- Runs analytical experiments in a methodical manner to find opportunities for product and process optimization.
- Assists in the presentation of business insights to management using visualization technologies and data storytelling.
- May partner with Data Architects, Data Analysts, Data Engineers and Visualization Experts to develop data-driven solutions for the business.
Benefits
- medical/prescription drug coverage (with a Health Savings Account feature)
- dental and vision options
- employee and spouse/child life insurance
- short and long-term disability protection
- 401(k) with PNC match
- pension and stock purchase plans
- dependent care reimbursement account
- back-up child/elder care
- adoption, surrogacy, and doula reimbursement
- educational assistance, including select programs fully paid
- a robust wellness program with financial incentives
- maternity and/or parental leave
- up to 11 paid holidays each year
- 9 occasional absence days each year, unless otherwise required by law
- between 15 to 25 vacation days each year, depending on career level; and years of service
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What This Job Offers
Job Type
Full-time
Career Level
Mid Level
