Skills this job asks for
Product managementA/B testingB2B salesStatisticsTableauLookerPower BISnowflake
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Sponsorship verdict
Sponsorship unlikely
Something in the evidence works against sponsorship. Read the reasons before you invest time.
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Employer is on a government sponsor recordThe US Department of Labor certified 17 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
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Existing work authorization requiredFrom the posting’s own wording.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- The US Department of Labor certified 17 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest May 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.
Before you apply
Review before applying
Existing work authorization required — the posting’s wording suggests candidates who already hold work rights. Read the original listing carefully.
These come from the posting’s own wording. Read the original listing to confirm. See better-fit alternatives →
About the role
PLEASE NOTE: This position is located in Charlotte, NC, Denver, CO, or Seattle, WA and requires attendance in office three days a week.
Candidates must be legally authorized to work in the United States. LendingTree and its affiliates (“LendingTree”) will not provide or assume sponsorship for employment visas for this position, now or in the future.
The Opportunity
Help make it easier for consumers to move through LendingTree’s online experience. As an Optimization Analyst, you’ll bring insurance industry experience to drive optimization ideas, manage the testing roadmap, and improve landing pages and web form flows. You’ll collaborate with stakeholders, conduct competitive analysis, and translate opportunities into testing hypotheses that reduce friction and increase conversion. Working with creative, technical, and analytics partners, you’ll launch experiments and turn findings into recommendations that support revenue growth.
How You’ll Make an Impact
• Proactively identify optimization opportunities through stakeholder collaboration, competitive analysis, and insights from the analytics team, then translate those ideas into actionable testing hypotheses.
• Manage the optimization testing roadmap, including priorities, timelines, and stakeholder alignment.
• Partner with the analytics team to estimate the revenue potential of proposed tests and prioritize opportunities based on business goals and expected impact.
• Execute A/B tests across landing pages and web form flows, partnering with creative teams on designs and technical teams on setup, quality assurance, tracking, and launch.
• Partner with the analytics team to monitor test and funnel performance, interpret results, and investigate unusual trends or tracking issues.
• Apply testing best practices and collaborate with analytics partners to recommend when tests should conclude or continue based on established testing guidelines.
• Prepare timely test recaps with input from the analytics team that explain findings, business impact, and recommended next steps to technical and nontechnical partners.
Who You’ll Work With
You’ll work closely with creative and front-end development teams to translate testing ideas into live experiments. You’ll collaborate with product and business stakeholders to generate ideas, align priorities, and manage the testing roadmap. You’ll also partner with the analytics team to understand funnel performance, interpret test results, and inform optimization decisions.
What You’ll Bring
• Bachelor’s degree in a relevant field or equivalent practical experience.
• Insurance industry experience.
• 1–2 years of experience in website optimization, digital experimentation, or a related role, including hands-on exposure to A/B testing.
• An understanding of conversion funnels and how testing can improve the online customer experience.
• The ability to manage a testing roadmap, coordinate timelines, and align stakeholders around priorities.
• The ability to collaborate with creative, front-end development, and analytics teams to launch experiments and translate findings into next steps.
What Will Help You Thrive
• B2B insurance experience is preferred.
• Curiosity about user behavior and a proactive approach to generating optimization ideas through stakeholder conversations and competitive analysis.
• Strong attention to detail in test setup, quality assurance, and reporting, along with the ability to organize work and manage competing priorities.
• Clear communication and a collaborative approach to working with multiple partners and explaining test findings to nontechnical audiences.
• Analytical skills, including familiarity with website performance metrics and basic statistical concepts used to evaluate experiments, are preferr
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