Principal Research Scientist [Risk]

WorldwideData & AIPrincipal / Staff
Gaji
Tidak dicantumkan
Tanyakan saat wawancara
Wilayah
Worldwide
Worldwide
Tipe kerja
Tidak disebut
Remote penuh
Level
Principal / Staff
Zona waktu
Fleksibel / tidak disebut
Diposting
Invalid Date
Dicek hari ini
Kenapa lowongan ini bisa dilamar dari Indonesia

Lokasi yang ditulis perusahaan: "Worldwide". Terbuka untuk kandidat dari mana saja (worldwide).

Keputusan akhir tetap di perusahaan. Baca deskripsi lengkap sebelum melamar.

Seberapa cocok CV-mu?

Unggah CV sekali, lalu cek skor kecocokan, kekuatan, dan kekurangan untuk setiap lowongan.

Masuk untuk cek

Keahlian yang disebut

Machine Learning

Benefit yang disebut

  • Cuti berbayar
  • Dana belajar
  • Kesehatan & wellness

Deskripsi pekerjaan

2 menit baca

About Plata

Plata is one of the fastest-growing fintech companies in the world. In just 3 years, we've grown to 3M+ customers and reached a $5B+ valuation. We're now strengthening our Risk & Decisioning core team and are looking for a Principal AI Engineer to set the technical bar and build best-in-class, production-grade models that materially move business metrics.

Why this role

  • You will own our foundation model program end to end - from research direction to models running in production and driving real credit decisions
  • Your models directly move the numbers that matter: cost of risk, approval rates, and portfolio NPV across a fast-scaling credit portfolio
  • You'll work with one of the richest financial datasets in LATAM billions of transactions and behavioral events across 3M+ customers, growing daily

Challenges that await you

  • Build an end-to-end foundation model over financial event sequences - transactions, credit bureau data, and in-app behavioral events with subsequent fine-tuning for downstream business tasks: underwriting (PD), credit limit strategy, fraud detection, collections, and propensity models
  • Drive technical decisions end-to-end: methodology → implementation → performance and latency → robustness, interpretability, and regulatory compliance
  • Take models from research to production: training infrastructure, evaluation frameworks, model serving, latency/cost optimization, and monitoring
  • Research state-of-the-art approaches in the industry, publish your own work, and speak at leading conferences
  • Mentor senior engineers and scientists; own technical standards for model development across the team (design reviews, evaluation methodology, deployment practices)
  • Communicate results clearly to cross-functional stakeholders: product, risk, business, and leadership

What makes you a great fit

  • Proven experience applying deep learning to sequential data - transformer architectures on event/transaction sequences strongly preferred, but not required
  • Strong foundation in mathematical statistics and probability theory
  • Deep understanding of machine learning algorithms (GBM, MLP, CNN, RNN, Transformers, etc.)
  • Experience taking large models to production: distributed training, model serving, latency/cost trade-offs
  • Ability to strike a reasonable balance between solution complexity and practical applicability
  • Strong mathematical or technical education - degree in mathematics, physics, or CS from a top technical university
  • Kaggle Competitions Master/Grandmaster or equivalent (a plus); experience developing models in banking or consumer lending (a plus)
  • Strong communication skills

Our ways of working

Innovative Spirit: a commitment to creativity and groundbreaking solutions

Honest Feedback: valuing open, transparent communication

Supportive Team: a strong, collaborative community

Celebrating Achievements: recognizing our wins together

High-Tech Environment: a team full of smart and revolutionary people who date to challenge the status quo of incumbent finances

Our benefits

  • Relocation support to one of our hubs - Mexico, Cyprus, Serbia, Spain with assistance for the employee and their family
  • Flexible work from one of our offices or remote
  • Healthcare coverage
  • Education budget: language lessons, professional training and certifications
  • Wellness budget: mental health and fitness activity reimbursements
  • Vacation policy: 20 days of annual leave and paid sick leave

Originally posted on Himalayas

Hitung gaji bersih dalam rupiah

Kotor per bulanRp0
Biaya transfer & kurs− Rp0
Perkiraan PPh 21 per bulan − Rp0
Diterima bersih per bulanRp0
Bersih setahunRp0

Perkiraan kasar: kurs USD Rp17.800; pajak dihitung sebagai penghasilan orang pribadi (tarif progresif PPh 21, dikurangi PTKP), tanpa NPPN, iuran BPJS, atau potongan lain. Bukan nasihat pajak; cek ketentuan terbaru atau konsultan pajak.

Buka kalkulator gaji lengkap →

Tips melamar

  1. Sebutkan lokasi dan zona waktumu di bagian atas CV, mis. Jakarta, Indonesia (GMT+7).
  2. Sesuaikan ringkasan CV dengan kata kunci di deskripsi, terutama Machine Learning.
  3. Tulis hasil kerja dengan angka (mis. "menangani 60 tiket/hari"), bukan hanya tugas.
  4. Perusahaan resmi tidak pernah meminta biaya untuk melamar atau wawancara.
Baca panduan CV untuk perusahaan luar negeri →
⚑ Laporkan lowongan ini

Lowongan serupa

Dipilih dari bidang, keahlian, dan level yang mirip.

Worldwide
WorldwideData & AIKontrak / freelance
  • Worldwide
PythonMachine Learning
Ditemukan kemarin · HimalayasLamar
Principal Research Scientist [Risk]Banco Plata, S.A., Institución de Banca Múltiple
Lamar