# Senior Data Scientist, Fraud Operations at Navan

> India · Senior · Analytics / Data science · open. Source: https://alderhq.app/jobs/greenhouse%3Atripactions%3A8287469 (read 2026-11-04).

## Facts (observed)

- Company: [Navan](https://alderhq.app/companies/navan)
- Location text: Bengaluru, IN; Bengaluru
- Where it can be done from (inferred): India (evidence: "Location lists "bengaluru"")
- Posted: 2026-10-16 (19 days ago)
- First seen by alder: 2026-11-02 · last verified: 2026-11-04
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://navan.com/careers/openings?gh_jid=8287469
- Skills listed (inferred): Python, Spark, Snowflake, SQL

## Pay and sponsorship

- Posted pay: not posted
- Market band for similar posted roles (India, n 3): p25 $52k, median $74k, p75 $146k
- Recognised sponsor (NL): registered as "Navan Netherlands B.V." (checked 2026-11-03, [register](https://ind.nl/en/public-register-recognised-sponsors/public-register-regular-labour-and-highly-skilled-migrants))
- Recognised sponsor (NL): registered as "Navan Netherlands Labs B.V." (checked 2026-11-03, [register](https://ind.nl/en/public-register-recognised-sponsors/public-register-regular-labour-and-highly-skilled-migrants))
- Licensed UK sponsor: registered as "Navan Labs UK Limited" (checked 2026-11-03, [register](https://www.gov.uk/government/publications/register-of-licensed-sponsors-workers))

## Description (the employer's text)

Navan is expanding its Fraud Risk Management team to build world-class fraud detection, prevention, and analytics capabilities supporting our rapidly growing travel and expense businesses. We are seeking a highly skilled and visionary Data Scientist, Fraud, to design and scale advanced data science solutions that protect Navan’s customers, platform, and financial ecosystem.

This is a strategic and hands-on role, where you’ll partner with other fraud strategy members, product, engineering, and data teams to design the ML features, build the rule workflow, build next-generation fraud models, develop actionable insights, and lead the application of AI/ML to mitigate emerging fraud threats both in expense card issuing and travel fraud. The ideal candidate combines deep technical expertise in machine learning and data systems with a strong understanding of payment, identity, and transactional fraud patterns.

Location: Bangalore, India

### What You’ll Do

- Lead the design and deployment of advanced ML features, build rule workflows to detect and prevent fraud across travel and expense.
- Lead the design and development of advanced ML and statistical models to detect, predict, and prevent fraudulent behavior across onboarding, payments, and expense workflows.
- Drive applied research in anomaly detection, network/graph modelling, real-time clustering, and link analysis to identify emerging fraud patterns and organized fraud rings.
- Partner cross-functionally with other Risk Strategy team members, Fraud operations, Engineering, and Product teams to translate insights into scalable prevention rules, thresholds, and model-driven interventions.
- Own model lifecycle management from feature engineering and experimentation to monitoring, model retraining, and post-deployment optimisation.
- Perform root-cause and loss attribution analyses, identifying vulnerabilities and quantifying financial impact to inform control effectiveness and business risk appetite.
- Sign up for the stretch fraud loss goals and the ability to drive the roadmap to meet the goal.
- Collaborate with Data Engineering and Platform teams to define data schemas, pipelines, and infrastructure that enable real-time fraud monitoring and analytics.
- Mentor junior data scientists and fraud analysts, providing technical guidance and driving excellence in experimentation, model governance, and reproducibility.
- Contribute to the overall fraud strategy roadmap, helping evolve Navan’s machine learning and analytics capabilities to stay ahead of emerging fraud trends.
- Partner with external vendors and third-party data sources to enrich detection signals and improve model precision and recall.
### What We’re Looking For

- 5+ years of experience in data science strategy, with a strong focus on fraud detection, risk modeling, or financial crime analytics.
- Master’s (must-have) or PhD (preferred) in Computer Science, Statistics, Applied Mathematics, or related quantitative field.
- Deep technical expertise in machine learning, predictive modelling, anomaly detection, and network analysis applied to fraud problems.
- Proficiency in Python, SQL, and modern ML libraries.
- Experience with large-scale data environments such as Snowflake, Databricks, Spark, or equivalent big data platforms.
- Strong understanding of payment processing, card networks, identity verification, and behavioural fraud typologies (e.g., synthetic identities, ATO, friendly fraud, first-party fraud, third-party fraud, scams).
Demonstrated success in developing and deploying ML models in production, including monitoring and score drift management.

- Familiarity with fraud detection tools, rule engines, and streaming data systems is a plus.
- Proven ability to communicate complex data science findings to technical and non-technical audiences, including executives.
- Experience collaborating in cross-functional teams that include Product, Engineering, and Fraud Operations.
Navan uses AI-assisted Automated Employment Decision Tool (Metaview) to assist with evaluating resumes against job qualifications for this role. All final decisions are made by human recruiters and hiring managers.

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/greenhouse%3Atripactions%3A8287469 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.