Senior Yield Data Analyst

Hearst•New York, NY

10d•$125,000•Hybrid

About The Position

Senior Yield Analyst Location: New York City, Hybrid Most yield roles are just babysitting clunky dashboards and running basic reports. This isn’t one of them. Hearst is seeking a hybrid data analyst and ad-tech expert to act as a force multiplier for our programmatic strategy. You’ll bypass rigid dashboards to dive into partner and log-level data, surfacing high-value insights across a footprint reaching hundreds of millions of users. Partnering with our engineering and BI teams, you will sit at the bleeding edge of addressability, dynamic optimization, and audience generation. If you want the autonomy to build robust data products and the runway to make a massive impact on a digital media giant, we want to hear from you. What You’ll Actually Do Drive Strategic Yield: Proactively hunt down issues, bidder discrepancies, and pricing inefficiencies by diving into raw, partner-level data. Cut Through the Noise: Build your own queries and scripts to bypass slow dashboards. Your goal is 90% insights, 10% data-gathering. Build the Future of Ad Tech: Hands-on involvement in log-level analytics, addressability, and dynamic ad optimization. Translate Data to Dollars: Speak fluent "engineering" to data teams and fluent "revenue" to executives, turning complex findings into actionable forecasts. Scale with AI: Use LLMs and automation to scale revenue analysis while acting as the "human-in-the-loop" for statistical integrity. Eliminate Technical Debt: Build optimized, clean internal data products and reproducible workflows rather than brittle, ad-hoc scripts. What You Bring to the Table Experience: 5+ years in a senior analyst, BI, or yield role within an advertising environment. Education: Quantitative degree (Math, Engineering, Stats, Econometrics, or Data Science). Ad-Tech Fluency: Deep understanding of GAM, DSPs, SSPs, header bidding, and inventory optimization. Technical Chops: Advanced SQL and Python . Ability to manipulate massive datasets and optimize for BigQuery performance. Anti-Fragility Mindset: You build things to last and naturally gravitate toward automating and bulletproofing workflows. Autonomous Execution: You don’t wait for a Jira ticket; you make independent analytical decisions that drive revenue strategy. Why Hearst? You will be working with a portfolio that shapes the daily media consumption of millions. We offer the scale and data resources of a massive publisher, combined with a team culture that values sanity and innovation. You will have the freedom to experiment, the mandate to innovate, and a direct line of sight into how your analysis drives the bottom line. Our Benefits: At Hearst Newspapers we not only support our employees through personal and professional development, but we also believe in promoting each individual’s physical, financial and emotional wellbeing (and that of their family). Our industry-leading benefits include: Physical Wellbeing: Medical, Dental, and Vision coverage to keep you and your family healthy. Invest for the Future: Competitive retirement plan with matching program in most markets. Generous Paid Time Off: Recharge with ample time off, including holidays and vacation. Paid Parental Leave: Support for growing families, with paid leave for new parents. Monthly Child & Dependent Care Reimbursement: Financial support for the care of your loved ones. Emotional Wellbeing: Be your best self with our mental wellness benefits. LGBTQ+ & Inclusive Health Services: Inclusive healthcare designed for every individual’s unique needs. Fertility Coverage & Menopause Support: Helping you along every step of your family journey. Pet Wellness Reimbursement & Rover Credits: We care about your pets, too – helping you keep them happy and healthy. And more, click here for additional benefits and details. About Hearst Newspapers: With 2,500 employees across the nation, HNP represents a network of 24 daily and 52 weekly publications, including the San Francisco Chronicle, Houston Chronicle, San Antonio Express-News and Albany Times Union, several top digital-only news and lifestyle sites, marketing services businesses, and entertainment businesses such as King Features Syndicate. At HNP, we are investing in new and innovative ways to tell stories–growing newsrooms, diversifying tools, evolving platforms–to support the millions of people who trust us each month to help them make decisions, take action and be inspired. Be a part of something bigger–Your Headline Awaits In accordance with applicable law, Hearst is required to include a reasonable estimate of the compensation for this role if hired in New York State. The reasonable estimate, if hired in New York State, is $125,000. Please note this information is specific to those hired in New York State. If this role is open to candidates outside of New York State, the salary range would be aligned to that specific location. A final decision on the successful candidate’s starting salary will be based on a number of permissible, non-discriminatory factors, including but not limited to skills and experience, training, certifications, and education.

Requirements

5+ years in a senior analyst, BI, or yield role within an advertising environment.
Quantitative degree (Math, Engineering, Stats, Econometrics, or Data Science).
Deep understanding of GAM, DSPs, SSPs, header bidding, and inventory optimization.
Advanced SQL and Python .
Ability to manipulate massive datasets and optimize for BigQuery performance.
Anti-Fragility Mindset: You build things to last and naturally gravitate toward automating and bulletproofing workflows.
Autonomous Execution: You don’t wait for a Jira ticket; you make independent analytical decisions that drive revenue strategy.

Responsibilities

Drive Strategic Yield: Proactively hunt down issues, bidder discrepancies, and pricing inefficiencies by diving into raw, partner-level data.
Cut Through the Noise: Build your own queries and scripts to bypass slow dashboards. Your goal is 90% insights, 10% data-gathering.
Build the Future of Ad Tech: Hands-on involvement in log-level analytics, addressability, and dynamic ad optimization.
Translate Data to Dollars: Speak fluent "engineering" to data teams and fluent "revenue" to executives, turning complex findings into actionable forecasts.
Scale with AI: Use LLMs and automation to scale revenue analysis while acting as the "human-in-the-loop" for statistical integrity.
Eliminate Technical Debt: Build optimized, clean internal data products and reproducible workflows rather than brittle, ad-hoc scripts.