Senior Data Scientist

Quona Capital; Bengaluru; On-site; INR 1,500,000 - 2,800,000; Full time

Job summary

Bureau is a unified risk decisioning platform for Compliance, Fraud, and Transaction risks, backed by a 1B+ identity graph. We seek a capable ML/DS engineer to build graph-ML models and deploy them at scale from Bengaluru.

You will design and deploy ML models for fraud and risk, run experiments, and ship production software with observability. Strong Python, cloud experience, and a track record in fintech-related domains are essential.

Qualifications

• BS/MS/PhD in ML, CS, Math, Stats, or related field (4–7 years).
• Strong Python programming and cloud experience (AWS/Databricks/Azure).
• Experience shipping production ML, especially in fraud/risk/payments/compliance.

Responsibilities

• Build and extend graph-native models to detect fraud and identity risk across networks.
• Design and deploy statistical, AI/ML, and deep learning models with real-time serving.
• Run experiments and data pipeline work to fine-tune model performance.
• Ship production-grade software with ML observability built in.

Skills

Python

Cloud platforms

SQL

DBT

Athena/BigQuery

Production ML

Graph modeling

Autonomy

Ambiguity tolerance

fintech domain exposure

Education

BS/MS/PhD in ML, CS, Math, Stats, or related field

Tools

Databricks

Azure

AWS

BigQuery

Job description

About Bureau

Bureau is a unified risk decisioning platform for Compliance, Fraud, and Transaction risks. Our platform is a single decision-making engine, powered by a 1 billion+ identity knowledge graph. Over 150 Banks, fintechs, retailers, and digital platforms use Bureau to verify identities faster and stop fraud earlier globally.

Bureau has raised $50M+ from renowned Silicon Valley and global investors including Sorenson Capital and PayPal Ventures and is expanding rapidly from APAC to Americas, Europe, and beyond.

Why Bureau?

Bureau is building the infrastructure that makes digital identities and transactions safe and trustworthy for billions of people. The mission is big, the problems are complex, and the impact is real.

We hire people who want that level of responsibility. People who move fast, build systems from scratch, and care deeply about turning strategy into execution. If you want predictability or narrow scope, this won't be your place. If you want to shape how a scaling global company operates—keep reading.

What You'll Do

• Build and extend graph-native models (GNNs, embeddings, and custom graph algorithms) to detect fraud, collusion, and identity risk across banking and e-commerce networks

• Design and deploy statistical, AI/ML, and deep learning models for fraud and risk, including real‑time serving

• Run experiments and light data pipeline work to fine‑tune model performance

• Ship production‑grade software backed by statistics and ML, with ML observability built in

What You'll Bring

• BS/MS/PhD in ML, CS, Math, Stats, or related field; 4 to 7 years in DS/AI/ML Engineering roles

• Strong Python; cloud experience (AWS/Databricks/Azure); SQL, DBT, Athena/BigQuery

• Track record shipping production ML, ideally in fintech fraud, risk, payments, or compliance

• Comfort with ambiguity, unlabelled data, and working autonomously to find business impact

• Prior graph‑modeling experience a plus

Our Culture

• We hire self‑motivated people and get out of their way

• We value performance, not hours worked

• Speed, ownership, and impact matter most

Compensation

• Competitive salary + potential equity

• Health benefits, flexible PTO, learning budget