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2 мСсяца Π½Π°Π·Π°Π΄

Data Scientist (Fintech)

85Β 000 - 135Β 000GBP
Π€ΠΎΡ€ΠΌΠ°Ρ‚ Ρ€Π°Π±ΠΎΡ‚Ρ‹
remote (Ρ‚ΠΎΠ»ΡŒΠΊΠΎ Europe)
Π’ΠΈΠΏ Ρ€Π°Π±ΠΎΡ‚Ρ‹
fulltime
Π“Ρ€Π΅ΠΉΠ΄
senior
Английский
b2
Π‘Ρ‚Ρ€Π°Π½Π°
UK/Poland/Spain +4 Π΅Ρ‰Π΅
Вакансия ΠΈΠ· списка Hirify.GlobalВакансия ΠΈΠ· Hirify Global, списка ΠΌΠ΅ΠΆΠ΄ΡƒΠ½Π°Ρ€ΠΎΠ΄Π½Ρ‹Ρ… tech-ΠΊΠΎΠΌΠΏΠ°Π½ΠΈΠΉ
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ОписаниС вакансии

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TL;DR

Data Scientist (Fintech): Designing and deploying data-driven solutions to combat identity and payment fraud with an accent on machine learning and graph analytics. Focus on building scalable production-ready models, developing risk mitigation strategies, and optimizing backend performance in collaboration with engineering.

Location: Remote from UK, Germany, Ireland, Spain, Poland, Bulgaria, or Lithuania

Salary: Β£85K - Β£135K

Company

A leader in fraud prevention and AML compliance utilizing device intelligence and AI to protect banks, retailers, and fintechs worldwide.

What you will do

  • Build and deploy machine learning models to prevent fraud across diverse fintech use cases.
  • Develop risk mitigation strategies and interventions to improve the user experience.
  • Work directly with clients to identify fraud challenges and deliver high-impact, data-driven solutions.
  • Evolve risk metrics and supporting datasets to measure the causal impact of initiatives.
  • Collaborate with engineering to scale models into production and optimize system performance.

Requirements

  • 7+ years of experience in data science or quantitative modeling, ideally in risk or fraud contexts.
  • Advanced degree in a quantitative field (Mathematics, Statistics, Computer Science, Engineering, Economics, etc.).
  • Strong working knowledge of Python, R, Spark, and SQL.
  • Proven ability to explain complex technical findings to non-technical stakeholders and clients.
  • Must be based in the UK, Germany, Ireland, Spain, Poland, Bulgaria, or Lithuania.

Culture & Benefits

  • Remote-first culture with a flexible "Work from Anywhere" approach.
  • Generous compensation including cash and equity with early exercise options.
  • Flexible paid time off and a designated year-end break.
  • Stipends for home office setup, monthly meals, social meet-ups, and wellness.
  • Annual learning budget for professional development.

Π‘ΡƒΠ΄ΡŒΡ‚Π΅ остороТны: Ссли Ρ€Π°Π±ΠΎΡ‚ΠΎΠ΄Π°Ρ‚Π΅Π»ΡŒ просит Π²ΠΎΠΉΡ‚ΠΈ Π² ΠΈΡ… систСму, ΠΈΡΠΏΠΎΠ»ΡŒΠ·ΡƒΡ iCloud/Google, ΠΏΡ€ΠΈΡΠ»Π°Ρ‚ΡŒ ΠΊΠΎΠ΄/ΠΏΠ°Ρ€ΠΎΠ»ΡŒ, Π·Π°ΠΏΡƒΡΡ‚ΠΈΡ‚ΡŒ ΠΊΠΎΠ΄/ПО, Π½Π΅ Π΄Π΅Π»Π°ΠΉΡ‚Π΅ этого - это мошСнники. ΠžΠ±ΡΠ·Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎ ΠΆΠΌΠΈΡ‚Π΅ "ΠŸΠΎΠΆΠ°Π»ΠΎΠ²Π°Ρ‚ΡŒΡΡ" ΠΈΠ»ΠΈ ΠΏΠΈΡˆΠΈΡ‚Π΅ Π² ΠΏΠΎΠ΄Π΄Π΅Ρ€ΠΆΠΊΡƒ. ΠŸΠΎΠ΄Ρ€ΠΎΠ±Π½Π΅Π΅ Π² Π³Π°ΠΉΠ΄Π΅ β†’