Manager, Data Science

Description

The Marketing Services Technology team is hiring a Data Science Manager to lead a globally distributed group of data scientists while also contributing directly to the team's data science goals.

The work covers the methods and models behind end-to-end marketing campaigns, from audience targeting and campaign execution to measurement. The platforms run at global scale, handling over 175 billion transactions and supporting data-driven marketing for financial institutions in markets worldwide. The aim is to show the right content to the right person at the right time.

The role suits people who want to shape the future of digital marketing technology through data science.

Responsibilities

• Work with global, cross-functional teams to design, build and maintain advanced analytics and data science solutions that have business impact.
• Propose and present creative solutions to challenges that are new to the company, to the financial industry and to data science.
• Research and assess emerging AI, machine learning and data science technologies, identifying both opportunities and risks.
• Measure, validate, deploy, monitor and improve internal and external machine learning models that produce actionable marketing insights.
• Apply machine learning methods (for example SVM, Random Forest, XGBoost, LightGBM and CatBoost), deep learning techniques (for example LSTM, RNN and Transformer) and LLMs to analytical problems.
• Turn advanced analytics, model results and experimental findings into clear, data-driven insights for senior business and product stakeholders.
• Design and build reliable data pipelines covering ingestion, aggregation and processing of large, high-dimensional datasets.
• Help develop and adopt frameworks, standards, best practices and guardrails that keep AI solutions responsible, compliant and resilient.
• Spot where data science capacity falls short of need and propose sustainable fixes that help the team.
• Communicate your vision and roadmap clearly and confidently, in writing and in speech, to a wide range of stakeholders.

Requirements

• Experience researching and adopting new technologies, especially in GenAI and agentic AI.
• Experience driving the development, validation, monitoring and ongoing improvement of predictive models, statistical techniques and algorithms tied to business goals.
• Experience with data management, mining, analytics, reporting, product development and quantitative analysis.
• Experience mentoring and coaching other data scientists.
• A strong academic background in computer science, data science, technology, mathematics, statistics or a related field, or equivalent work experience.
• Proficiency in Python, Spark, Hadoop platforms (Hive, Impala, Airflow, NiFi) and SQL.
• Working knowledge of machine learning frameworks, libraries, data structures and software architecture.
• Familiarity with technologies such as GenAI, LLMs, agentic AI, TensorFlow, Sklearn and Pandas.
• Experience with BI platforms such as Tableau or Power BI is a plus.
• Strong analytical skills and a proven ability to turn data into compelling insights.
• Experience working with stakeholders to understand technical needs and deliver solutions that fit.
• Ability to explain the business value of products and contribute to the marketing toolset.
• Everyone working with the company assets, information or networks is responsible for information security. This means following security policies and practices, protecting the confidentiality and integrity of the information you access, reporting any suspected breach or violation, and completing all required periodic security training.