Manager, Marketing Data Science Enterprise Product & Technology

$110,000 - $140,000/Yr

Dow Jones - New York, NY

Full-time - Mid Level

New York, NY

Chemical Manufacturing

About the position

The Manager of Marketing Data Science at Dow Jones will play a crucial role in executing the company's investment in next-generation marketing data science and analytics for Enterprise clients. This position involves collaborating with various teams to streamline data utilization, enhance marketing effectiveness, and improve customer profiling and retention through advanced analytics and machine learning.

Responsibilities

• Collaborate with Technology teams to establish and maintain robust data infrastructure, ensuring data quality, accessibility, and security.
• Work with ML Ops teams to ensure proper model implementation infrastructure for marketing modelers.
• Ensure data governance, quality, privacy, and security standards are met while developing and implementing data strategies that align with business goals.
• Utilize reporting and querying tools to leverage customer data for actionable insights to optimize marketing strategies and personalize campaigns.
• Collaborate with cross-functional teams to understand business needs and translate them into data-driven solutions.

Requirements

• 7+ years experience in data science, data engineering, and/or marketing analytics preferred.
• Degree in a quantitative field such as Data Science, Computer Science, or related disciplines.
• Proficiency in a programming language such as Python, R, or SQL.
• Experience with cloud data store platforms such as AWS, Databricks, Snowflake, Big Query, and ETL tools.
• Familiarity with marketing automation platforms, CRM systems, and digital analytics tools.
• Experience with data visualization and reporting tools such as Tableau, Looker, or Power BI.
• Strong business acumen and ability to communicate complex concepts to non-technical audiences.
• Understanding of marketing principles, customer segmentation strategies, and digital marketing channels.

Nice-to-haves

• Understanding of data modeling principles and ML operations.

Benefits

• Comprehensive Healthcare Plans
• Paid Time Off
• Retirement Plans
• Comprehensive Insurance Plans
• Lifestyle programs & Wellness Resources
• Education Benefits
• Family Care Benefits & Caregiving Support
• Commuter Transit Program
• Subscription Discounts
• Employee Referral Program