OverviewThis is a remote role that may only be hired in the following location(s): AL, AR, CT, DE, IA, ID, IN, KS, KY, LA, ME, MS, NC, NE, NM, NV, OH, OK, OR, PA, RI, SC, SD, UT, VA, WV
This Senior Data Scientist position will be a key member of the Direct Bank team and is responsible for developing, enhancing, maintaining, and operationalizing analytical models used to inform strategic business decisions. The role will focus primarily on Marketing Attribution and Deposit Pricing, supporting initiatives that improve customer acquisition, optimize pricing decisions, deepen customer relationships, and maximize deposit growth and profitability.
This position will support the development of advanced analytical solutions to shape the strategic direction of data-driven initiatives across the Bank. The role requires expertise in large-scale data structuring and computations, data source investigation, model development, performance monitoring, and process optimization to drive innovation across the Bank. The individual will be expected to translate complex analytical findings into practical business recommendations for senior leaders and cross-functional stakeholders.
The successful candidate will bring a strong combination of technical depth, financial services acumen, and business consulting skills. This role requires hands-on experience with statistical modeling, machine learning, data visualization, and storytelling, as well as the ability to partner with Marketing, Product, Pricing, Finance/Treasury, Risk, Technology, and Data Engineering teams.
Responsibilities- Business Strategy - Lead or participate in moderately complex initiatives and deliverables by utilizing data-driven, advanced analytical, statistical techniques, algorithms, and models. Direct the data gathering, data processing, and data mining of large and complex data sets to support Direct Bank growth, pricing, and profitability objectives.
- Support the development and maintenance of Marketing Attribution models, including channel performance, multi-touch attribution, media mix modeling, campaign lift measurement, customer acquisition cost, conversion analysis, and return on marketing investment.
- Support the development and maintenance of Deposit Pricing models, including rate sensitivity, elasticity analysis, balance forecasting, promotional offer analysis, retention modeling, competitive rate benchmarking, and customer-level pricing response.
- Develop algorithms using advanced mathematical and statistical techniques, including machine learning, to predict customer behavior, deposit flows, campaign response, balance movement, retention risk, and business outcomes.
- Provide recommendations that help optimize marketing spend, improve acquisition efficiency, balance deposit growth and margin, and inform pricing decisions across savings, money market, CD, and other deposit products.
- Partner with business leaders to frame analytical problems, define success measures, identify trade-offs, and translate model outputs into actionable strategies.
- Reporting - Analyze and produce timely reports for senior management and other stakeholders regarding risks, trends, patterns, opportunities, and exceptions across marketing performance and deposit portfolio behavior.
- Develop recurring and ad hoc reporting related to marketing attribution, channel effectiveness, funnel conversion, campaign performance, deposit growth, pricing effectiveness, customer retention, balance migration, and profitability trends.
- Support the development of business intelligence and analytical reporting using data visualization technologies, including dashboards, scorecards, executive summaries, and self-service reporting tools.
- Use data storytelling to communicate complex statistical and machine learning outputs to non-technical audiences of varying levels, including senior executives and business partners.
- Monitor model performance and business outcomes over time, identify changes in customer behavior or market dynamics, and recommend model refinements or strategy adjustments as needed.
- Collaboration - Responsible for supporting all components of project execution and stakeholder engagement. Works across departments and with functional management as needed to recommend timelines, set expectations, and ensure analytical deliverables are aligned to business priorities.
- Partner closely with Marketing teams to evaluate campaign effectiveness, optimize channel mix, improve targeting strategies, and measure incremental impact.
- Partner with Product, Pricing, Finance/Treasury, and Risk teams to evaluate deposit pricing strategies, understand balance sheet implications, and support customer and portfolio-level decisioning.
- Partner with Technology, Data Engineering, and Data Governance teams to define data requirements, investigate source systems, improve data quality, and support scalable data pipelines.
- Lead, mentor, and support associate team members by providing guidance on analytical methodology, code review, documentation, model interpretation, and stakeholder communication.
- Understand business needs and changes in the competitive environment to provide thought leadership around data science activities that support Direct Bank growth and profitability.
- Operational Support - Serve as an advisor on designing, refining, and delivering modeling best practices for Marketing Attribution and Deposit Pricing analytics. Provide support to the department and staff regarding technical inquiries, model interpretation, and data processes.
- Promote best practices for model development, validation support, documentation, version control, governance, reproducibility, monitoring, and ongoing maintenance.
- Investigate data anomalies, source system issues, model drift, and reporting discrepancies; recommend process improvements to enhance reliability and efficiency.
- Support analytical process optimization, including automation of recurring workflows, standardization of metrics, and enhancement of reusable modeling assets.
- Maintain awareness of emerging analytics, machine learning, and AI capabilities, including potential applications of Large Language Models to improve productivity, insight generation, and decision support.
QualificationsBachelor's Degree and 8 years of experience in Banking, financial or other directly related industry. OR High School Diploma or GED and 12 years of experience in Banking, financial or other directly related industry.
Preferred Area of Study: Computer Science, Statistics, Data Science, Mathematics, Economics, Finance, Engineering, or a related quantitative discipline.
Preferred Skills:
- Experience with Marketing Attribution methods, including multi-touch attribution, media mix modeling, campaign lift measurement, incrementality testing, channel optimization, customer journey analytics, and marketing ROI measurement.
- Experience with Deposit Pricing analytics, including rate elasticity, balance forecasting, customer sensitivity modeling, retention analysis, promotional pricing, competitive benchmarking, and portfolio profitability analysis.
- Experience with machine learning and advanced statistical modeling techniques such as regression, classification, clustering, time series forecasting, causal inference, propensity modeling, uplift modeling, segmentation, and optimization.
- Experience with data visualization tools such as Tableau, Power BI, or similar platforms.
- Experience with Large Language Models (LLMs), generative AI, or AI-enabled analytics workflows is preferred.
- Able to analyze, structure, clean, transform, and visualize large sets of data from multiple internal and external sources.
- Able to create and apply accurate algorithms to datasets to identify solutions, quantify business impact, and recommend optimal actions.
- Knowledge of programming languages and data platforms including but not limited to SQL, Python, R, Oracle, SAS, MATLAB, Snowflake, Databricks, or cloud-based analytics environments.
- Proficiency in statistics and statistical packages/applications used to analyze data sets and evaluate model results.
- Strong communication skills, including the ability to explain technical concepts, analytical assumptions, business trade-offs, and model limitations to non-technical stakeholders.
- Strong business acumen with an understanding of Direct Banking economics, digital acquisition channels, deposit products, pricing strategy, customer behavior, and competitive dynamics.
- Ability to manage multiple priorities, work independently, influence stakeholders, and deliver high-quality analytical work within established timelines.
- Advanced degree in a quantitative discipline is preferred but not required.
Benefits are an integral part of total rewards and First Citizens Bank is committed to providing a competitive, thoughtfully designed and quality benefits program to meet the needs of our associates. More information can be found at https://jobs.firstcitizens.com/benefits.
