Senior Marketing Analyst

Tabby is hiring a Senior Marketing Analyst for a remote role open to applicants in Serbia. Level rates it ; you can apply on Tabby.

Level's read on this job

On Level's scale, this marketing role is Little AI ●○○○: aI is not part of the work.
This is listed as a remote role.
Level classes it as a senior role.
Tabby has 43 other open roles on Level.
Posted in the last few days.

AI in this role

Tabby creates financial freedom in the way people shop, earn and save by reshaping their relationship with money. Over 25 million users choose Tabby to stay in control of their spending and make the most out of their money.

The company’s flagship offering allows shoppers to split their payments online and in-store with no interest or fees. Over 70,000 global brands and small businesses, including Amazon, Noon, IKEA, and SHEIN use Tabby to accelerate growth and gain loyal customers by offering easy and flexible payments online and in stores.
Tabby generates over $18 billion in annual transaction volume for its partner brands and is the highest-rated, most-reviewed, largest, and fastest-growing FinTech in the GCC region.

Tabby launched in 2019 and has since raised +$1 billion in equity and debt funding from global and regional investors, and is now valued at $6,5 billion.

About the role

As the Senior Marketing Analyst for CRM, you will be the single analytics owner of CRM - the person marketers come to as a partner. You will own how campaigns are measured, how the communication data is built and trusted, and how insights turn into decisions: what to stop, scale, or fix.

You will work closely with CRM marketers, Product, and the data platform team. You define what data you need and accept its quality; you do not build the pipelines yourself.

What you will be doing

Be the analytics partner to CRM marketers and Product on every initiative. Work with them on how to improve results.
Answer "how do we correctly measure CRM activity" questions: choosing the right measurement design for a campaign type (always-on journeys vs one-off blasts vs product launches), defining what "delivered" means per channel, and defending the methodology to stakeholders
Explain the technical side in plain language: how an experiment works, what a holdout is for, why a number can or cannot be trusted, so marketers make decisions they actually understand
Own how CRM performance is measured: control groups, holdouts, A/B tests
Own the CRM analytics data in dbt on BigQuery: who gets which message, on which channel, for which product, and how often
Be the customer of the data platform team: say what data you need from the CRM and attribution tools, agree on timelines, and sign off on quality. You own what the numbers mean; they build the pipelines.
Build Tableau dashboards that earn their place: visualisations stakeholders can open to check a hypothesis, answer their own question, or spot an insight in minutes.
Keep the self-serve AI analytics assistant up to date, so non-technical colleagues can get answers to simple questions and run their own ad-hoc analysis without waiting for an analyst
Work with a data science team, ask the right questions about a recommendation or propensity model, spot when it is not doing its job, and drive the test that proves it

What you will need

3+ years of experience as a data/marketing/CRM analyst, with exposure to CRM, lifecycle, or retention analytics
Strong SQL and hands-on dbt experience (we run dbt on BigQuery); experience designing and maintaining data models, not just querying
Experience with CRM engagement platforms: Customer.io, MoEngage, Braze, Iterable or similar: you understand journeys, events, profile attributes, and delivery semantics
Solid experience with marketing experimentation: holdout design, global static control groups, control group integrity, A/B tests, incrementality vs attribution
Proficiency in Python
Proficiency in Tableau (or similar BI tool)
Proactive ownership: you find problems in data and processes before stakeholders do, audit your domain independently, and bring your own agenda and ideas on how to achieve business goals.
Thinking partnership: stakeholders should be able to brainstorm with you, not just hand you tasks.
First-time-right quality: numbers you ship are trusted without a second verification pass;

Nice-to-have

You now how Uplift modeling and causal ML works and can create MVP version
Propensity / churn / LTV modeling

How we rate this

Senior Marketing Analyst at Tabby rates 24 out of 100 for how much of the daily work is AI. That makes it Little AI (AI Level 1 of 4). The level is about AI in the job, not seniority.

Classification

Little AI. AI is not part of the work.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.