VP Marketing Data Science

Overview
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.

This pivotal role will be responsible for leading advanced analytics initiatives and developing sophisticated measurement models to optimize marketing spend and drive demonstrable business impact. The successful candidate will be 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.

Key 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 multiple data sources (media channel data, acquisitions data, revenue data, digital data) to 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 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 deployment of models.

Serve as a subject‑matter expert in analytics, drive ideation on analytical projects and simplify outcomes for stakeholders.

Qualifications

6‑10 years of experience within media measurement and analytics, preferably in financial services, client side, agency side or publisher side.

Proficiency in Python and R and experience with relevant data science libraries and frameworks.

Experience with big data technologies, cloud platforms and data visualization tools such as SQL, Tableau, Power BI and Dataiku.

Hands‑on experience with complex structured and unstructured marketing data and leading predictive modeling using machine learning, deep learning and neural networks across multiple projects.

Strong understanding of core AI/ML concepts (RNN, LSTMs, LLMs, NLP) and ability to identify the optimal solution for any business case.

Ability to independently own and project‑manage workstreams involving multiple stakeholders, demonstrating accountability and decisiveness.

Ready for hands‑on involvement in measurement to identify roadblocks, uncover solutions, operate with curiosity and be hypothesis‑driven.

Process‑oriented, organized and able to deliver high‑quality work in a fast‑paced dynamic environment across teams.

Extensive experience working closely with legal, compliance and procurement teams on technology contracting and approvals in a highly regulated environment.

Tools and Platforms: proficient in Python/R, Hive/SQL; experience with machine learning frameworks like TensorFlow, PyTorch; good to have experience on Gen AI platforms and tools.

Education
Masters or Bachelor’s degree in Business Analytics, Finance, Statistics (advanced degree preferred).

Benefits
Citi offers competitive benefits including medical, dental and vision coverage; 401(k); life, accident and disability insurance; wellness programs; paid time off packages (vacation, sick leave, paid holidays). For additional information, please visit citibenefits.com.

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

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