Outricher / research / brighty-app · ICP dataset · Customer Success / Support Lead

Customer Success / Support Lead: who will build support on the line of regulatory risk.

This is a candidate dataset for the ICP from report #5 — the fifth of six roles. For a licensed crypto-fiat neobank, support is not a cost center but the front line of regulatory risk: complaints, AML/KYC escalations, freezes, chargebacks — and, at the same time, the primary retention channel. Brighty is reposting Support Specialist ×4 — the team is growing chaotically, without a managed layer. For this role we assembled a live, verified, contactable pool of support specialists and leaders from fintech, crypto and local CEE payment donor companies — focused on exactly the level Brighty is actually hiring for. Not a raw list from open search, but data engineering built around a specific hiring task: who, why now, and how we found them — honestly, including what cannot be found directly.

1,639
CS specialists in Brighty's hiring zone
587
in the dataset, enriched (avg 134 fields)
449
rising specialist→lead (primary bet)
324
active in support right now (+232 alumni)

prepared 2026-06-28 · MEASURED · Outricher data

01The hiring task: what is actually being reposted

Report #5 makes it clear: support / customer success is the 2nd most frequent function in Brighty's hiring (13 of 68 postings, after Compliance/AML). And the key honest finding from the data: what gets reposted is not a "Lead" but "Customer Support Specialist (B2C)" ×4 in LT and the UAE. In other words, the actual open demand is for Mid-level specialists, not a ready-made manager. The Support Lead conclusion is not what the vacancies literally say — it is a grounded structural inference: with that stream of specialist reposts, the team scales reactively, without a managed layer that has metrics and escalation into Compliance.

That is why our primary bet is the rising specialist→lead: it closes both the current gap (agents hired one at a time) and the future managed layer, and it lowers the repost frequency itself. A ready-made Head is offered as a separate tier — for those who need a management layer immediately. Below are 1,639 CS specialists already working at Brighty's donor companies, by name and with contacts.

02The universe: where we source from

Current support / success / CX employees (from Head of Support and CX Lead down to Senior Support Specialist) at Brighty's donor companies — fintech, crypto and local CEE payment services (Paysera, Genome, Walletto, WhiteBIT — exact geo match), across the geography where Brighty actually hires (EU/EEA + Switzerland + UK + UAE; LT/LV/PL/EE and Dubai are its hubs). This is an honest "floor" for the named set of companies — the full graph is larger.

Donor companyCS specialists (current, in hiring zone)
Revolut717
Crypto.com412
TransferGo117
Klarna79
Bitpanda59
Coinbase45
Paysera40
Nexo36
bunq31
N2624
Blockchain.com21
Binance17
Genome17
Monzo14
Gemini6
Walletto2
WhiteBIT1
Kraken1
Total (before quota and deduplication)1,639
CEE donors — an exact geo hit. Paysera, Genome, Walletto, WhiteBIT are local Lithuanian-Latvian fintech/crypto companies running multilingual B2C support right in Brighty's hubs (LT/LV). They are absent from standard company directories — we resolved them by domain specifically for this task. This is the lowest-noise, most geo-precise segment: the candidate already lives where Brighty hires and knows the local specifics.
Honest about method: multilingualism and tooling are a boost, not a filter. Language skills (EN + a local language required) and tool proficiency (Zendesk / Intercom / CSAT / SLA) are fields that are filled in for only ~26% of profiles in the graph. Filtering the search hard on them would discard 3 out of 4 valid candidates simply because a person did not list a language in their profile. So we apply a hard filter only on title + geo + domain (reliable, well-populated fields), and detect multilingualism, tooling and metrics in the profile text, awarding points for them as a ranking boost. That gives 195 in the pool with an explicit language signal, 61 with tooling (Zendesk/Intercom), 66 with metrics (CSAT/SLA) — but the absence of a signal does not drop a candidate, because the data is incomplete, not the person weak.
Honest about status: who is in the role now, and who is an "alumnus". We tie a candidate to a donor company by their support role — but the person may have moved on since. So we check the current title and split the pool explicitly: 324 are active in support right now (outreach to them reads "I see you're in CS at [company]"), 232 are "CS alumni" (they were in support at a donor and are now in an adjacent role — a warm, domain-relevant lead, but the outreach is honestly framed as "you were in CS"). This is not a guess — it is a comparison of the matched role against the live profile headline. Both segments are tagged in the dataset with the cs_current_status field and split into separate CSVs.

An honesty caveat: the warm Revolut corridor (Brighty's CTO came from there, ×6 on the team) is real, but it is an engineering channel, not a support channel — from Revolut we take only profiles with an explicit support title, not "for the fact they worked there". Bloodline gives cultural fit, not domain relevance for support.

03Two tiers: the primary bet is the rising middle

Exactly what matches the real demand: Brighty reposts specialists, so the primary bet is the rising specialist→lead (budget-friendly, high ceiling). A ready-made Head is offered as a separate tier.

Tier B — Rising specialist→lead · 449 people ★ PRIMARY BET

Senior Support Specialist / Support Team Lead / Customer Success Manager with 2–4 years in B2C fintech or crypto — just outgrew the agent role, took a first team or group-lead, but does not yet hold a Head title and has not moved to big tech. Knows the domain, is tool-proficient, multilingual, and needs the next step — which the current employer may not offer. Cheaper than a ready-made Head; with the right onboarding, will fill the Support Lead role in 6–12 months and grow with Brighty. This is the answer to the actual demand: it is precisely the specialist level that gets reposted. Of these, 231 have held their role for ≥3 years without an upgrade — a structural signal of "stuck, ready for the next step".

CandidateCurrent roleDonorGeoTenure in roleScore
Anna Tkach Senior Customer Support Specialist – SME Support Zendesk / Intercom multilingual TransferGo Poland 1 yr A+ 13
Dariia Dolhova Customer Support Specialist Zendesk / Intercom multilingual TransferGo Poland 3.2 yr A+ 13
David Nagy Customer Care Specialist Zendesk / Intercom multilingual Bitpanda Austria 4.1 yr A 12.5
Giorgi Merebashvili Product Support Specialist Zendesk / Intercom Revolut Poland 0.9 yr A 12
Gintarė Remeikė Customer Support Automation Specialist Zendesk / Intercom multilingual TransferGo Lithuania 2.6 yr A 12
Ilona Zelena Mid Bussiness Customer Support Specialist multilingual Revolut Poland 0.9 yr A 12
Kacper Witczak Technical Support Specialist - SME (Mid) multilingual Revolut Poland 1.8 yr A 12
Fatima Hajji Customer support specialist French & English Zendesk / Intercom multilingual TransferGo Poland 2 yr A 12
Rafael Morgado Customer Care Technology Lead multilingual Bitpanda Austria 3.2 yr A 11.5
Martin Emilov Customer Support Quality Assessment Specialist Zendesk / Intercom Nexo Bulgaria 4.5 yr A 11.5

The "Zendesk / Intercom" badge = a support tool was found in the profile; "multilingual" = at least one language besides English is listed. This is not a hypothesis, it is a row in the file.

Tier A — Senior / Proven · 104 people

Already hold the Head of Support / Customer Support Lead / CX Lead / Customer Success Lead role, or a Support/Success Manager with a team, at a licensed fintech or crypto company. They can build the managed layer immediately — set up SLA/CSAT/FRT, tiers, a knowledge base, escalation into Compliance, and hire and onboard agents. Of these, 104 are at the Head/Lead/Manager level of support right now. More expensive, but this buys readiness of the managed layer, not potential — for those who need a line manager immediately.

CandidateCurrent roleDonorGeoTenure in roleScore
Michael Khoo Head of Customer Support Enablement Zendesk / Intercom multilingual Bitpanda Austria 4.3 yr A+ 16.5
Anna Harmash Head of Customer Care Zendesk / Intercom multilingual TransferGo Lithuania 4.7 yr A+ 16
Inga Aukselyte Head of Customer Care multilingual TransferGo Lithuania 5.4 yr A+ 15
Gerda Grigenaite Customer Support Team Lead Zendesk / Intercom multilingual TransferGo Lithuania 5.4 yr A+ 15
Alyce Bargery People Support Lead Zendesk / Intercom Klarna Sweden 7.5 yr A+ 14.5
Jogile Steikunaite Customer Support and Work Flow Management Team Lead Zendesk / Intercom multilingual TransferGo Lithuania 0.9 yr A+ 14
Alexandru Ursache Customer Success Manager - Social Media Zendesk / Intercom multilingual Revolut Romania 1.7 yr A+ 13.5
Liam Seaman Team Lead - Customer Care and Community Zendesk / Intercom Bitpanda Austria 2.6 yr A+ 13.5
Martim Castro Team Lead Customer Success Manager Zendesk / Intercom multilingual Revolut Spain 0.7 yr A+ 13.5
Jessica Ferreira Customer Experience Manager Zendesk / Intercom multilingual Revolut Portugal 1.2 yr A+ 13.5

CAVEAT: the senior tier fills the managed layer immediately, but if budget matters more than speed, the rising middle — with onboarding — fills the same role in 6–12 months more cheaply. Choosing a tier means choosing "readiness now" versus "budget + loyalty".

04Why they are ready to move right now

Readiness to move is not a guess — it is detected structurally from the career data.

Stuck (long tenure)

231 of 587 have held their current role for ≥3 years without a title change. In a large neobank, a front-line agent / junior-lead grows slowly because of the sheer size of the org. At Brighty the same person gets a broad scope of responsibility and a direct Lead→Head path. For a mid-level candidate this is the main pull trigger.

CEE locality

171 candidates live in LT/LV/PL/EE — Brighty's hubs — plus 7 in Dubai (the 2nd hub). Zero/minimal relocation, local languages, market knowledge. This is the lowest-risk, fastest hire — the candidate is already where the company hires.

Crypto-native

247 already work in crypto-fintech: they understand freezes, chargebacks, KYC holds, and the specifics of crypto-operation tickets. For a crypto-fiat neobank this is critical — no need to explain why verification takes time or why a balance is "stuck".

Tooling and metrics

61 with an explicit Zendesk / Intercom footprint and 66 with metrics (CSAT / NPS / SLA / FRT) — these are people who did not just "answer tickets" but built the function: processes, tiers, measurable quality. Exactly what it takes to turn a chaotic line into a managed one.

How we found the "function builders". The "built support" signal almost never sits in the profile headline — it lives in the descriptions of past roles ("rolled out Zendesk", "cut FRT by 30%", "built escalation tiers"). We read not just the current title but the entire career history of each candidate — which is why the tooling and metrics footprint is found in ~5× more profiles than a single-headline search would surface. This is the difference between a "keyword list" and data engineering built for the task.

05Composition of the dataset

Broken down by function within the pool, it is clearly a structured customer-support funnel, not "everyone under the word support".

FunctionPeopleShare
Customer Support / Success (IC)39968%
Support / Success Manager (team)7913%
Senior Support Specialist (rising)509%
Adjacent (support-transferable)285%
Head / Lead of Support / CX254%
Adjacent (CS-alumni, now non-CS role)61%

An honest finding: the broad word "support" also covers IT support, support engineers (devops) and sales support — we deliberately excluded them with a negative filter at the search stage so the pool contains only customer-facing roles. The "rising specialist→lead" layer (50 people) is the direct answer to Brighty's reposted specialist demand.

Geography (top 8)

Bulgaria
133
Lithuania
87
Poland
82
United Kingdom
60
Austria
35
Germany
31
Sweden
30
Ireland
22

06What you receive as a file

The full dataset: JSONL / CSV / Excel + ready-made segments. Each profile carries career depth, education, skills, location, contacts (where available), score and tier. Quality is measured, not claimed.

  1. leads.xlsx — Excel with all 152 fields for 587 candidates.
  2. leads.csv / leads.jsonl — for CRM and programmatic processing.
  3. segments/ — ready-made slices: rising specialist→lead (primary bet), senior-proven, CS-lead-ready, tooling signal, metrics, multilingualism, crypto-native, CEE-local, Dubai hub, stuck-and-ready, warm Revolut channel, with email, and one per donor.
Request this dataset: Request this dataset ↗ — 587 candidates, all formats + segments.
Quality metricValue
Profiles in the dataset587
Fields per profile (min · avg · max · union)95 · 134 · 151 · 152
Outreach-ready (email / phone / profile)100%
Email (combined)26.9% (158)
With a tooling / multilingualism signal61 / 195
Hot A+/A98

We provide email and phone only from verified sources — where there is none, the value is NULL; we do not fabricate contacts. Languages and tools are a signal from the profile text under partial field population (~26%): the absence of a mark ≠ the absence of a skill, so do the final check at the interview. Depth can be raised with targeted contact re-enrichment for the chosen tier.

07Where to go from here

This is a sample of what we do for any of the 6 roles from report #5 — and for any company. Name the role and the tier and we will build the next dataset in the same format: a verified pool, scoring, segments, contacts, evidence.

★ Already available: AML / MLRO · CISO / Information Security · CFO / finance · UX Lead / design · Customer Success (this one). Next: Data Analyst — the last role is being built the same way.

Want a report like this for your company?

Tell us your target company or ICP and we'll deliver the dataset + a short analysis in the same format.

Request your report — hi@outricher.com ↗
Outricher · professional graph of 1.17B profiles · @outricher · hi@outricher.com
MEASURED · Outricher data · 2026-06-28