VP Marketing Data Science

Citi; New York (NY); On-site; USD 129,840 - 194,760; Full time

Benefits offered by this job

Medical, dental, and vision coverage

401(k)

Paid time off and sick leave

Job summary

Citi is looking for a VP, Marketing Data Science in New York, New York, to join the Media Sciences team. This senior role requires expertise in advanced analytics with a focus on marketing effectiveness and audience analysis. The individual will design complex models, lead predictive analytics, and translate data insights into strategic recommendations for senior stakeholders.

The ideal candidate should have over six years of experience in media measurement and analytics, proficiency in Python and R, and a strong understanding of machine learning frameworks. Citi offers competitive benefits in addition to a robust compensation package ranging from $129,840 to $194,760 annually.

Qualifications

• 6-10 years’ experience in media measurement and analytics, preferably in financial services.
• Experience with big data technologies and cloud platforms.
• Extensive experience with structured and unstructured marketing data.

Responsibilities

• Design and implement advanced statistical and machine learning models.
• Utilize predictive analytics to forecast marketing outcomes and inform budget allocation.
• Communicate complex analytical concepts to senior leadership and teams.

Skills

Python

R

Machine Learning

Data Visualization

SQL

Education

Masters or Bachelor's degree in Business Analytics, Finance, or Statistics

Tools

TensorFlow

PyTorch

Dataiku

Tableau

Power BI

Job description

The VP, Marketing Data Science is a highly experienced and senior role, part of the larger Media Sciences team in the Client Org, reporting to the SVP Marketing Data Science. This role will primarily perform advanced analytics on data from the clean room, marketing data analytics, audience analytics, creative analysis, consumer journey, attribution and scenario planning. The VP will lead advanced analytics initiatives and develop sophisticated measurement models to optimize marketing spend and drive demonstrable business impact. The successful candidate is a strategic thinker with deep expertise in data science, marketing analytics, and a proven track record of translating complex data into actionable insights for senior stakeholders.

Responsibilities

• Design, develop, and implement advanced statistical and machine learning models to analyze marketing effectiveness, cross‑channel attribution, audience analytics, and user journey analytics.
• Leverage multiple analytical approaches, tools, and techniques on diverse data sources (media channel data, acquisitions data, revenue data, digital data), conduct A/B testing and incrementality studies, addressing business questions through a marketing lens.
• Utilize predictive analytics to forecast marketing outcomes, identify optimal spending levels, and inform budget allocation decisions.
• Translate complex business questions into analytical problems and guide the team in developing data‑driven solutions.
• Communicate complex analytical concepts and data‑driven insights clearly and concisely to diverse audiences, including senior leadership, marketing teams, and cross‑functional partners.
• Oversee the end‑to‑end model development lifecycle, from data collection and preprocessing to model building, validation, and deployment.
• Ensure the team adheres to best practices in data science, model governance, and ethical data usage, and ensure timely and effective deployment of models.
• Serve as a subject‑matter expert in analytics, understanding complex business problems, developing analytical approaches to solve them, simplifying outcomes for stakeholders, and driving ideation on analytical projects.

Qualifications

• 6‑10 years’ experience within media measurement and analytics, preferably in financial services, client side, agency side, or publisher side.
• Proficiency in programming languages such as Python and R, and experience with relevant data science libraries and frameworks.
• Experience with big data technologies, cloud platforms, and data visualization tools (e.g., SQL, Tableau, Power BI, Dataiku).
• Hands‑on experience working with complex structured and unstructured marketing data and leading predictive modeling using Machine Learning, Deep Learning/Neural Networks across multiple projects.
• Strong understanding of core AI/ML concepts (e.g., RNN, LSTM, LLM, NLP) and ability to identify the optimal solution for any business case.
• Ability to independently own and project manage workstreams involving multiple stakeholders, showing strong sense of accountability and decisiveness with a strong work ethic.
• Prepared for hands‑on involvement in measurement to identify roadblocks, uncover solutions, operate with curiosity, and be hypothesis‑driven.
• Process oriented and organized, able to deliver high‑quality work in a fast‑paced, dynamic environment across different teams.
• Extensive experience working closely with legal, compliance, and procurement teams on technology contracting and approvals in a highly regulated environment.

Skills & Platforms

• Proficient in Python / R, Hive / SQL.
• Experience with machine learning frameworks such as TensorFlow, PyTorch, etc.
• Good to have: Experience with Gen AI platforms and tools.

Education

Masters or Bachelor’s degree in Business Analytics, Finance, or Statistics; an advanced degree is preferred.

Location

New York, New York, United States.

Compensation

$129,840 - $194,760 annually.

Benefits

Citi offers competitive employee benefits, including medical, dental and vision coverage, 401(k), life, accident, and disability insurance, wellness programs, paid time off, vacation, sick leave, and paid holidays. Additional discretionary and formulaic incentive and retention awards may be available for eligible employees.

Equal Opportunity Statement

Citi is an equal opportunity employer, and qualified candidates will receive consideration without regard to their race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or any other characteristic protected by law.