Data Scientist

Bureau; Bengaluru; On-site; INR 1,400,000 - 2,000,000; Full time

Benefits offered by this job

Health benefits

Flexible PTO

Learning budget

Job summary

Bureau is hiring a data-science oriented ML Engineer in Bengaluru to build features for graph-native models used to detect fraud and identity risk. You will write production-quality Python, work with SQL data, and collaborate with senior data scientists to train, evaluate, and deploy models while improving ML observability and pipeline quality.

Ideal candidates have 1–3 years in DS/AI/ML roles, a strong foundation in ML/CS, and comfort with ambiguous data.

Qualifications

• 1–3 years in DS/AI/ML Engineering roles (internships with shipped work count).
• Strong Python and SQL; cloud exposure is a plus.
• Experience taking a model towards production is a plus.

Responsibilities

• Build and maintain features for graph-native models (GNNs, embeddings, graph algorithms).
• Support design/train/evaluation of ML models for fraud and risk under guidance.
• Run experiments, clean data, and tune model performance.
• Write production-quality code and build ML observability.
• Document work for team reuse.

Skills

Python

SQL

ML fundamentals

Education

BS/MS in ML/CS/Math/Stats

Tools

Databricks

AWS

Azure

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 maintain features and components for graph-native models (GNNs, embeddings, graph algorithms) used to detect fraud, collusion, and identity risk

• Support the design, training, and evaluation of statistical, AI/ML, and deep learning models for fraud and risk, under a senior data scientist's guidance

• Run experiments, clean and prepare data, and do light pipeline work to help tune model performance

• Write production-quality code backed by statistics and ML, and help build out ML observability for the models you work on

• Document your work clearly enough that others on the team can pick it up

What You'll Bring

• BS/MS in ML, CS, Math, Stats, or a related field; 1 to 3 years in DS/AI/ML Engineering roles (internships with real shipped work count)

• Strong Python; working knowledge of SQL; exposure to a cloud platform (AWS/Databricks/Azure) is a plus

• Some experience taking a model from a notebook toward something production-adjacent, ideally with fraud, risk, payments, or compliance data — but we'll take strong fundamentals over domain experience

• Comfort with ambiguity and unlabelled data, and the initiative to ask questions and look things up rather than wait to be told

• Prior exposure to graph-based thinking (even coursework or personal projects) is a plus, not a requirement

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