Marketing Manager

Quantic School of Business and Technology•Washington, DC

About The Position

We are hiring a Marketing Manager to join the two teams that take a prospective student from first ad click to registered student at our next-generation graduate school. This is an entry-level role. You will work across direct response marketing and admissions operations: pulling and building reports, QA-ing ads, emails, and landing pages, maintaining CRM and scheduling tools, and taking on the ad hoc projects that keep both teams moving. Marketing owns demand: paid campaigns across LinkedIn, Meta, and Google, the landing pages they drive to, and the lifecycle messaging that turns a lead into an applicant. Admissions team owns the applicant: the interview team, candidate communications, interview scheduling, and every stage from application through interview, consult, and registration. This role sits between the two. We are not hiring for experience. We are hiring for raw intelligence, work ethic, and AI fluency. You should already use Claude, ChatGPT, or similar tools every day and want to use them all day: to draft, to analyze, to QA, to learn a new tool in an afternoon, and to automate the work that does not need a human. Everything else about marketing and admissions can be taught, and we will teach it.

Requirements

Bachelor's degree or equivalent, with 0 to 2 years of work experience. New graduates are encouraged to apply.
Daily, hands-on use of Claude, ChatGPT, or similar tools, and a clear point of view on where they help and where they fail.
Strong writing and editing. You can draft a clean email and you catch the error everyone else missed.
Comfortable with spreadsheets and data: formulas, pivot tables, and basic charts. Exposure to SQL, Python, or Looker Studio is a plus, not a requirement.
Fast learner of new tools and systems. You can pick up Airtable, Customer.io, or an ad platform from documentation and a short walkthrough.
Organized and reliable on recurring work. Reports go out on schedule, every time.
Curious about marketing, education, or both.

Nice To Haves

Prior exposure to paid media, CRM tools, or admissions is a plus, not a requirement.

Responsibilities

Pull weekly and monthly performance reports across LinkedIn Ads, Meta, and Google Ads: spend, leads, cost per application, and conversion by segment.
QA every ad, landing page, and email before it ships: copy, links, UTMs, pixels, and rendering on mobile.
Build and update campaign assets in the ad platforms: audiences, ad copy variants, naming conventions, and UTM taxonomy.
Research newsletter placements, audiences, and new tools, and bring back a written recommendation.
Keep campaign documentation current: what is live, what it targets, and what it says.
Learn the admissions process end to end: application, invite to interview, interview, consult, and registration, and the Airtable fields and views behind each stage.
Maintain Calendly configuration and interviewer availability so capacity matches demand across the US and RoW.
Monitor interview schedule and conduct rates, flag no-show patterns, and help test the reminder and confirmation copy that lifts them.
Support Customer.io flows: build and QA new sends, check personalization logic and links, and keep flow documentation current.
Review Help Scout inquiry themes and feed common questions back into CRM messaging and FAQs.
Own recurring funnel reporting: stage-by-stage counts, conversion rates, and week-over-week change, delivered on a fixed schedule.
Build one-off analyses on request, for example interview conduct rates by cohort or registration rates by applicant segment.
Keep the numbers honest: reconcile sources, note data gaps, and say when a result is inconclusive.
Take on project and task work from marketing and admissions leadership, scope it, and ship it with a clear write-up.
Recent examples: audit a week of Help Scout replies for typos, map a Zoom-to-Airtable interview notes pipeline, test headline variants on a landing page.
Document what you build so someone else can run it.
Reach for an LLM by default: draft, edit, summarize, analyze, write a formula or script, and pressure-test your own logic before it reaches a person.
QA consistently. AI output is only as good as the check behind it. We run 200+ active ads with zero typos because every one is audited. You will hold that standard.
Do the due diligence on new tools. Evaluate an AI feature or tool, test it on real work, and write up whether we should adopt it.
Automate the repeatable: reports, QA checks, data syncs, and reply drafts. If you do a task three times, ask whether an agent should do it the fourth.
Show your work. Keep prompts, scripts, and workflows documented and reusable so the team compounds what you build.