Marketing Mix Optimization – Principal Data Scientist at Citizens Bank

, , United States -

Full Time

Start Date

Immediate

Expiry Date

11 May, 26

Salary

0.0

Posted On

10 Feb, 26

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Marketing Analytics, Data Science, Optimization, Python, Statistical Modeling, Machine Learning, Forecasting, Time Series Analysis, Decision Support, Analytical Tools, Collaboration, Problem Solving, Communication, Financial Modeling, Scenario Planning, Constraint Design

Industry

Banking

Description

There’s no better time to be a Citizen! We are growing and looking to add to our Marketing Analytics team. The Marketing Analytics team supports Enterprise Marketing with data, analytics, and insights that inform our customer marketing and product strategy across all Lines of Businesses. Marketing Analytics is responsible for analyzing the performance of marketing campaigns across online and offline channels and provides analytical support throughout the marketing campaign lifecycle including pre-campaign sizing, list production, experimental test design, measurement, optimization, and forecasting. We are seeking a Principal Data Scientist with strong analytical and algorithmic skills to optimize our marketing investment strategies. In this role, you will design and build advanced decision support systems that facilitate scenario planning for marketing investment decisions, including constrained optimization solutions that leverage a suite of marketing mix models. You will develop relationships with other data scientists as well as partners in Marketing, Product, Finance and Technology Services to collaboratively deliver transformational optimization capabilities. Primary responsibilities include: Architect and develop marketing investment optimization frameworks that translate marketing mix models and other analytic outputs into actionable budget allocation and scenario planning across channels, products, markets and time. Design and implement non‑linear, constrained optimization solutions that incorporate real‑world business constraints (e.g., budgets, channel minimums/maximums, pacing, and strategic priorities) to support high‑stakes marketing investment decisions. Serve as a technical authority on optimization and decision science, guiding best practices in objective function formulation, constraint design, solver selection, and performance validation. Partner closely with Marketing, Finance, Product, and Technology stakeholders to frame business questions into well‑defined optimization problems and translate analytical results into clear, decision‑ready recommendations. Build robust, scalable decision support tools that enable repeatable scenario analysis and are suitable for operational use by analytics, marketing and business teams. Lead the strategic roadmap for marketing optimization capabilities by identifying gaps, prioritizing enhancements, and aligning analytical solutions with evolving business needs. Required Skills/Experience: 8+ years of experience in quantitative analytics including marketing analytics, financial modeling, applied statistics, or equivalent. 4+ years of experience delivering quantitative decision tools for business applications. Proven experience turning business problems into rigorous analytic solutions by applying critical thinking and advanced technical & statistical programming techniques. Expertise in Python with 5+ years of applied experience. Proficient with one or more optimization modeling packages and solvers (e.g. GAMS/CONOPT, CPLEX, SCIP, Pyomo, SciPy). Expertise translating statistical models into scenario planning and optimization and solve non-linear, constrained optimization problems. A deep understanding of the theory and application of a variety of statistical and machine learning methods and algorithms, including optimization under uncertainty, forecasting, time series analysis, and Bayesian methods Additional Skills/Experience: Strong sense of ownership, relentless curiosity, and self-driven approach to problem solving. Experience in data and analytics in Banking and Financial Services Strong written and verbal communication skills required with an ability to successfully communicate analytic results, insights, and resulting business implications to technical and non-technical audiences. Ability to work in a team environment and collaborate with colleagues who have a background in statistics, database development/maintenance, and information technology. Education, Certifications and/or Other Professional Credentials: Master’s degree in operations research, computer science, engineering, mathematics, statistics, or similar quantitative field required Hours and Work Schedule: Hours per Week: 40 Work Schedule: Monday – Friday Hybrid: 4 days per week in office Equal Employment Opportunity Citizens, its parent, subsidiaries, and related companies (Citizens) provide equal employment and advancement opportunities to all colleagues and applicants for employment without regard to age, ancestry, color, citizenship, physical or mental disability, perceived disability or history or record of a disability, ethnicity, gender, gender identity or expression, genetic information, genetic characteristic, marital or domestic partner status, victim of domestic violence, family status/parenthood, medical condition, military or veteran status, national origin, pregnancy/childbirth/lactation, colleague’s or a dependent’s reproductive health decision making, race, religion, sex, sexual orientation, or any other category protected by federal, state and/or local laws. At Citizens, we are committed to fostering an inclusive culture that enables all colleagues to bring their best selves to work every day and everyone is expected to be treated with respect and professionalism. Employment decisions are based solely on merit, qualifications, performance and capability. Equal Employment and Opportunity Employer Job Applicant Data Privacy Policy Background Check Any offer of employment is conditioned upon the candidate successfully passing a background check, which may include initial credit, motor vehicle record, public record, prior employment verification, and criminal background checks. Results of the background check are individually reviewed based upon legal requirements imposed by our regulators and with consideration of the nature and gravity of the background history and the job offered. Any offer of employment will include further information.

Responsibilities

The Principal Data Scientist will architect and develop marketing investment optimization frameworks and design non-linear, constrained optimization solutions. They will also partner with various stakeholders to translate business questions into optimization problems and deliver actionable recommendations.