Marketing Analyst - Network Optimization

Gen Digital Inc.•New York, NY

1d•$95,000 - $120,000

About The Position

The Marketing Analyst – Network Optimization will use data and experimentation to uncover what drives marketplace performance, turning analysis into clear, actionable recommendations that shape the strategy, execution, and continuous improvement of tests. This role sits at the intersection of marketing analytics, data science, product, and commercial strategy. The ideal candidate is comfortable working in a fast-paced environment, moving quickly from questions to analysis to action. At the core of the role: translating business questions into testable hypotheses, designing sound experiments, monitoring live tests, and delivering clear, data-driven readouts that inform optimization decisions — supported by day-to-day management of the test agenda.

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 the 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 to understand changes in 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 the development and maintenance of a prioritized test-and-learn agenda across network optimization, offer display, ranking, curation, pricing, eligibility, and related marketplace levers.
Translate business opportunities and performance signals into clear hypotheses, test objectives, target populations, success metrics, and guardrail metrics.
Help design A/B, holdout, multivariate, and other controlled experiments in partnership with Product, Engineering, Data Science, and business stakeholders.
Coordinate test setup, launch readiness, audience splits, documentation, timelines, and stakeholder communication.
Track execution from initial idea through implementation, launch, monitoring, analysis, and final recommendation.
Work quickly and pragmatically while maintaining analytical rigor and attention to detail.
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 such as 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 that require investigation or follow-up testing.
Build and maintain recurring reports, dashboards, and scorecards for the test pipeline, experiment status, and business impact.
Communicate findings clearly to technical and non-technical audiences, including marketing, product, finance, operations, and leadership.
Maintain a current view of the test pipeline, including 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 standards for experiment documentation, naming, tracking, and knowledge sharing.
Capture and distribute learnings so that successful approaches can be scaled and unsuccessful approaches can inform future tests.