Marketing Analyst - Network Optimization

Gen Digital Inc.•New York, NY

3d•$95,000 - $120,000

About The Position

The Marketing Analyst – Network Optimization uses data and experimentation to identify drivers of marketplace performance and turn analysis into actionable recommendations that inform strategy, execution, and ongoing test improvement. The role sits at the intersection of marketing analytics, data science, product, and commercial strategy. The analyst translates business questions into testable hypotheses, designs and monitors experiments, delivers clear data-driven readouts, and manages the day-to-day test agenda. The role includes marketplace and funnel analysis; support for test design, execution, and prioritization; reporting on experiment performance; and coordination with cross-functional stakeholders to move tests from proposal through launch, analysis, and follow-up. The analyst helps maintain reliable measurement, repeatable testing processes, clear documentation, and shared learnings.

Requirements

Bachelor’s degree in marketing analytics, statistics, economics, business, mathematics, computer science, or a related quantitative field.
1–3 years of experience in marketing analytics, product analytics, growth analytics, experimentation, revenue analytics, or a related discipline.
Experience working with A/B tests, holdout tests, campaign measurement, or other forms of controlled experimentation.
Working knowledge of experimental design, including hypotheses, control and treatment groups, success metrics, guardrails, and basic power or sample-size concepts.
Strong analytical skills and proficiency with SQL or Python, Excel, or a comparable data analysis tool.
Ability to create clear reports, dashboards, presentations, and written test readouts.
Strong attention to detail and ability to manage multiple concurrent workstreams.
Ability to work effectively in a fast-paced, ambiguous, and cross-functional environment.
Clear written and verbal communication skills.

Nice To Haves

Experience with experimentation or reporting platforms such as GrowthBook, Eppo, Optimizely, VWO, Looker, Tableau, or similar tools.
Familiarity with marketplace, lending, advertising, e-commerce, lead-generation, or other two-sided platform businesses.
Exposure to funnel analysis, offer ranking, pricing, partner optimization, customer segmentation, or revenue optimization.
Experience coordinating cross-functional projects or maintaining a structured test backlog.
Experience presenting analytical findings and recommendations to business stakeholders.

Responsibilities

Conduct exploratory analysis of customer behavior, traffic quality, offer engagement, and downstream outcomes.
Monitor marketplace and funnel performance to identify optimization opportunities across customer experience, offer display, partner performance, and monetization.
Support opportunity sizing and business-case development for proposed optimization initiatives.
Partner with analytics and data science teams to improve measurement quality, data reliability, and experimentation velocity.
Help develop repeatable processes for rapid testing, post-test analysis, and continuous optimization.
Support development and maintenance of a prioritized test-and-learn agenda covering network optimization, offer display, ranking, curation, pricing, eligibility, and related marketplace levers.
Translate business opportunities and performance signals into hypotheses, test objectives, target populations, success metrics, and guardrail metrics.
Help design A/B, holdout, multivariate, and other controlled experiments with Product, Engineering, Data Science, and business stakeholders.
Coordinate test setup, launch readiness, audience splits, documentation, timelines, and stakeholder communication.
Track tests from initial idea through implementation, launch, monitoring, analysis, and final recommendation.
Monitor live experiments and summarize performance across key funnel and marketplace metrics.
Produce concise, decision-oriented test readouts covering methodology, results, limitations, learnings, and recommended next steps.
Analyze metrics including impressions, click-through rate, conversion, click-to-funded rate, revenue, revenue per lead, revenue per click, and partner or network efficiency.
Identify meaningful changes, anomalies, and emerging opportunities requiring investigation or follow-up testing.
Build and maintain recurring reports, dashboards, and scorecards for the test pipeline, experiment status, and business impact.
Communicate findings to technical and non-technical audiences across marketing, product, finance, operations, and leadership.
Maintain a current view of proposed, approved, in-flight, completed, and follow-up experiments.
Manage meeting materials, action items, owners, dependencies, decisions, and timelines for the test agenda.
Help prioritize experiments based on expected impact, confidence, reach, effort, strategic importance, and learning value.
Coordinate with partner teams to resolve blockers and keep experiments moving toward launch and readout.
Maintain consistent experiment documentation, naming, tracking, and knowledge-sharing standards.
Capture and distribute learnings so successful approaches can be scaled and unsuccessful approaches can inform future tests.
Work quickly and pragmatically while maintaining analytical rigor and attention to detail.