Manager, Data Analytics & Forecasting

Dow Jones•New York, NY

4d•Onsite

About The Position

The Dow Jones Data Science team is looking for a Data-driven Analytics & Insights Manager with a strong foundation in statistics, experimentation, and marketing analytics, known for turning complex data into clear, actionable strategies that drive measurable revenue growth, profitability, and customer lifetime value. Expert at partnering with marketing, product, and finance to define the right questions, design robust analyses and tests, and translate findings into decisions that move key KPIs. Comfortable working across large, messy datasets and modern analytics stacks, with a track record of building scalable reporting, forecasting, and insight frameworks that improve decision quality at all levels of the organization.

Requirements

Bachelor's or Master’s degree in Economics, Finance, Data Science, Marketing Analytics, or equivalent experience.
7-10 years of experience in Marketing Analytics focused on the Media Industry
Advanced proficiency in statistics and experimentation (A/B testing, hypothesis testing, regression, segmentation, forecasting, causal inference) to support confident decision-making.
Hands-on experience building KPI frameworks, measuring success of business strategies , scalable dashboards and forecasting models that improve visibility into performance and enable proactive course correction.
Advanced proficiency in Python, R , SQL, Excel, and other statistical tools
Strong communication skills, including experience presenting to senior stakeholders
Ability to work under tight deadlines

Responsibilities

Revenue-focused analytics: Connects data work directly to business outcomes → conversion, retention, ARPU, CLV, ROAS, payback
Statistical rigor: Hands-on with hypothesis testing, experiment design, regression, segmentation, forecasting, and causal inference concepts.
Subscription & growth analytics: Deep experience measuring and optimizing campaigns, business strategies, funnels, pricing, and personalization across channels.
Storytelling with data: Distills complex analyses into simple narratives and visuals that influence senior stakeholders and drive decisions.
Roadmapping & prioritization: Builds clear analytics roadmaps aligned to business priorities
Team leadership: Coaches analysts, sets standards for quality and speed, and creates a culture of curiosity and impact.