Data Analyst
Tbilisi, Georgia
- Pay
- Pay not listed
- Work setting
Hybrid — work setting source
Location type: Hybrid
From the employer’s posting- Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting- Team
Operations — team source
Department: Operations
From the employer’s posting
Before you apply
- Sponsorship
Visa sponsorship not confirmed — sponsorship source
Will you require visa or employer sponsorship to work in this role, either now or in the future?
From the employer’s application form
What you’ll work on
Full postingPave Bank is a digital bank built for businesses that operate globally, with a client base concentrated in digital asset trading venues, payment providers, stablecoin issuers and fintechs.
We are looking for a Data Analyst who will sit inside the Commercial team and turn client, transaction and pipeline data into decisions.
Analyse client revenue, transaction volumes and payment corridors to find growth
Build and maintain client profitability and unit economics models
Design and own the Commercial team's dashboard layer and self-serve reporting
Build internal tools such as client scoring and pricing calculators, hosted on Google Cloud
Build AI-assisted workflows into Commercial processes and set AI standards for the team
From the employer’s posting
Pave Bank is a digital bank built for businesses that operate globally, with a client base concentrated in digital asset trading venues, payment providers, stablecoin issuers and fintechs. Our Commercial team owns the client relationship from first conversation through to ongoing revenue growth.
We are looking for a Data Analyst who will sit inside the Commercial team and turn client, transaction and pipeline data into decisions. This is not a reporting role where you wait for requests and return a spreadsheet. You will build the dashboards, the models and the internal tools that the Commercial team uses every day, and you will ship them yourself.
Analyse client revenue, transaction volumes, payment corridors and product usage to show where growth is actually coming from
Build and maintain client profitability and unit economics models, including fee income, correspondent costs and FX spreads
Design and own the the Commercial team's dashboard layer, covering revenue, pipeline, client activity and product adoption
Build internal tools that solve real Commercial problems, for example client scoring, pricing calculators, lead enrichment, reporting automation and data quality checks
Build AI assisted workflows into Commercial processes
What you’ll bring
All qualificationsCore experience
- Strong SQL, comfortable writing complex queries against large transaction datasets without hand holding
- Understanding of payments mechanics, including SWIFT, SEPA, correspondent banking, card scheme settlement or stablecoin flows
- Python for analysis and for building small applications and services
- Experience with dbt, Airflow or similar transformation and orchestration tooling
- Hands on experience with Google Cloud, including deploying and hosting an application, for example Cloud Run, Cloud Functions, App Engine, BigQuery, Cloud Scheduler
- Familiarity with CRM data models and pipeline analytics
Qualification wording
Strong SQL, comfortable writing complex queries against large transaction datasets without hand holding
Understanding of payments mechanics, including SWIFT, SEPA, correspondent banking, card scheme settlement or stablecoin flows
Python for analysis and for building small applications and services
Experience with dbt, Airflow or similar transformation and orchestration tooling
Hands on experience with Google Cloud, including deploying and hosting an application, for example Cloud Run, Cloud Functions, App Engine, BigQuery, Cloud Scheduler
Familiarity with CRM data models and pipeline analytics
Tools in this posting
- Python
- SQL
- BigQuery
- dbt
- Looker
- Metabase
- Power BI
- Tableau
- Airflow
- React
- Streamlit
- GCP
Source — Tool mentions in context
- Strong SQL, comfortable writing complex queries against large transaction datasets without hand holding - Python for analysis and for building small applications and services - Hands on experience with Google Cloud, including deploying and hosting an application, for example Cloud Run, Cloud Functions, App Engine, BigQuery, Cloud Scheduler
- Minimum 3 years in an analytical role, ideally in fintech, payments, banking or a data heavy commercial environment - Strong SQL, comfortable writing complex queries against large transaction datasets without hand holding - Python for analysis and for building small applications and services
- Python for analysis and for building small applications and services - Hands on experience with Google Cloud, including deploying and hosting an application, for example Cloud Run, Cloud Functions, App Engine, BigQuery, Cloud Scheduler - Demonstrated experience building dashboards in a modern BI tool, for example Looker Studio, Metabase, Tableau or Power BI
- Understanding of payments mechanics, including SWIFT, SEPA, correspondent banking, card scheme settlement or stablecoin flows - Experience with dbt, Airflow or similar transformation and orchestration tooling - Familiarity with CRM data models and pipeline analytics
- Hands on experience with Google Cloud, including deploying and hosting an application, for example Cloud Run, Cloud Functions, App Engine, BigQuery, Cloud Scheduler - Demonstrated experience building dashboards in a modern BI tool, for example Looker Studio, Metabase, Tableau or Power BI - Practical, daily use of AI coding tools. You should be able to walk us through something you built with Claude Code or an equivalent agent, and explain what you delegated and what you reviewed yourself
- Familiarity with CRM data models and pipeline analytics - Front end skills sufficient to build a usable interface, for example React or Streamlit - Exposure to digital assets or a regulated banking environment
- Build internal tools that solve real Commercial problems, for example client scoring, pricing calculators, lead enrichment, reporting automation and data quality checks - Deploy and host those tools on Google Cloud, and keep them running - Automate recurring manual work in the Commercial workflow instead of absorbing it
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Aug 28, 2026 · 55 days ago
- Recorded sightings
- 27
- Last seen by us
- Oct 22, 2026
- Employer says posted
- Aug 26, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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Job description
About the role
Pave Bank is a digital bank built for businesses that operate globally, with a client base concentrated in digital asset trading venues, payment providers, stablecoin issuers and fintechs. Our Commercial team owns the client relationship from first conversation through to ongoing revenue growth.
We are looking for a Data Analyst who will sit inside the Commercial team and turn client, transaction and pipeline data into decisions. This is not a reporting role where you wait for requests and return a spreadsheet. You will build the dashboards, the models and the internal tools that the Commercial team uses every day, and you will ship them yourself.
We expect you to work with AI as a default part of how you build. If you currently do everything by hand and see AI tooling as optional, this role will not suit you.
What you will do
Commercial analytics
Analyse client revenue, transaction volumes, payment corridors and product usage to show where growth is actually coming from
Build and maintain client profitability and unit economics models, including fee income, correspondent costs and FX spreads
Track pipeline health, conversion rates, time to onboard and time to first transaction, and explain the movements behind the numbers
Identify at risk clients through changes in activity patterns, and identify cross sell and upsell opportunities across the book
Support pricing decisions with evidence, including scenario modelling for fee changes and volume tiers
Prepare data for board, investor and management reporting, and be able to defend every number in it
Dashboards and reporting
Design and own the the Commercial team's dashboard layer, covering revenue, pipeline, client activity and product adoption
Move the team away from manual spreadsheets towards live, self serve reporting that people actually open
Define metrics clearly and consistently, and document them so the definitions do not drift between teams
Work with Operations, Finance, Compliance and Product to make sure the underlying data is trustworthy
Tooling and automation
Build internal tools that solve real Commercial problems, for example client scoring, pricing calculators, lead enrichment, reporting automation and data quality checks
Deploy and host those tools on Google Cloud, and keep them running
Automate recurring manual work in the Commercial workflow instead of absorbing it
Write clean, documented, maintainable code that someone else on the team can pick up
AI adoption
Use Claude Code and similar agentic tools as your primary build environment for analysis, tooling and automation
Build AI assisted workflows into Commercial processes, for example summarising client interactions, drafting first pass commercial documents and structuring unstructured data
Set the standard for AI usage inside the Commercial team, share what works, and help colleagues adopt it
Apply good judgement on where AI output needs human verification, particularly for anything client facing or regulatory
What we are looking for
Essential
Minimum 3 years in an analytical role, ideally in fintech, payments, banking or a data heavy commercial environment
Strong SQL, comfortable writing complex queries against large transaction datasets without hand holding
Python for analysis and for building small applications and services
Hands on experience with Google Cloud, including deploying and hosting an application, for example Cloud Run, Cloud Functions, App Engine, BigQuery, Cloud Scheduler
Demonstrated experience building dashboards in a modern BI tool, for example Looker Studio, Metabase, Tableau or Power BI
Practical, daily use of AI coding tools. You should be able to walk us through something you built with Claude Code or an equivalent agent, and explain what you delegated and what you reviewed yourself
Advanced spreadsheet skills, including modelling and Google Sheets automation
Strong commercial instinct. You care about why the number moved, not only what it is
Fluent professional English, written and spoken, is mandatory. Our working language is English and you will present analysis directly to senior stakeholders and clients. Georgian is an advantage but not a substitute
Nice to have
Understanding of payments mechanics, including SWIFT, SEPA, correspondent banking, card scheme settlement or stablecoin flows
Experience with dbt, Airflow or similar transformation and orchestration tooling
Familiarity with CRM data models and pipeline analytics
Front end skills sufficient to build a usable interface, for example React or Streamlit
Exposure to digital assets or a regulated banking environment
How we work
Small team, wide scope. You will own your work end to end rather than hand specifications to someone else
AI first by default. We expect meaningful output volume from a small headcount, and AI tooling is how we get there
Direct access to decision makers. Good analysis changes what we do, quickly
Bias to shipping. A working tool used by the team beats a perfect design nobody uses
Source details
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Tbilisi, Georgia
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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