---
title: 'Staff Data Scientist at Oscilar'
canonical: 'https://feeny.ai/job/staff-data-scientist-oscilar-remote-9wbyza65v3z4'
type: 'job'
last_seen: '2026-09-09'
---

# Staff Data Scientist at Oscilar

- **Company:** Oscilar
- **Location:** Remote
- **Employment:** full-time
- **Work type:** remote
- **Posted:** 2026-09-01
- **Last confirmed live:** 2026-09-09
- **Apply:** https://jobs.ashbyhq.com/oscilar/a83cfe5b-5a34-4aa7-9e4d-52ca6428efc6

## Job description

Shape the future of trust in the age of AI At Oscilar, we're building the most advanced AI Risk Decisioning™ Platform. Banks, fintechs, and digitally native organizations rely on us to manage their fraud, credit, and compliance risk with the power of AI. If you're passionate about solving complex problems and making the internet safer for everyone, this is your place https://oscilar.com/careers.

Why join us:

- Mission-driven teams: Work alongside industry veterans from Meta, Uber, Citi, and Confluent, all united by a shared goal to make the digital world safer.
- Ownership and impact: We believe in extreme ownership. You'll be empowered to take responsibility, move fast, and make decisions that drive our mission forward.
- Innovate at the cutting edge: Your work will shape how modern finance detects fraud and manages risk.

## JOB DESCRIPTION

As a Data Scientist at Oscilar, you will be responsible for developing and implementing advanced fraud detection models to protect our customers’ business from fraudulent activities. As an early member in the ML team you will have great impact in building out our ML stack.

## RESPONSIBILITIES:

- Develop and implement advanced fraud detection models, leveraging machine learning and statistical techniques, to identify and prevent fraudulent activities across our platform.
- Collaborate with cross-functional teams, including engineering, product, and operations, to design and implement fraud detection systems and processes.
- Analyze large volumes of data to identify patterns, trends, and anomalies indicative of fraudulent behavior, and develop data-driven insights to improve fraud prevention strategies.
- Evaluate the performance of existing fraud detection models and systems, and continuously optimize and update them to adapt to changing fraud trends and tactics.
- Stay up-to-date with the latest trends and advancements in fraud detection, data science, and machine learning, and apply this knowledge to enhance our fraud prevention capabilities.
- Communicate complex data analysis and model performance results to both technical and non-technical stakeholders, driving data-driven decision-making across the organization.
- Ensure data privacy and security compliance in all aspects of fraud detection and data analysis.

## REQUIREMENTS:

- 3+ years of experience in data science, machine learning, or a related field, with a focus on fraud prevention and/or anti-money laundering.
- Proficiency in Python.
- Fluency in cloud development (AWS, GCP, Azure, etc.) and MLOps is a plus.
- Strong knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection.
- Experience working with large datasets using distributed systems like Apache Spark and Dask, handling data-related challenges such as data cleaning, data quality, and data transformation and feature engineering at scale.
- Excellent analytical and problem-solving skills, with the ability to derive actionable insights from complex data.
- Strong communication skills, with the ability to explain complex concepts and findings to both technical and non-technical audiences.
- Ability to work independently and collaboratively in a fast-paced, dynamic startup environment.

## PREFERRED QUALIFICATIONS:

- Experience in the fintech, marketplaces, or financial services industry.
- Knowledge of current fraud tactics and trends, as well as experience with fraud detection tools and systems.

## BENEFITS

- Compensation: Competitive salary and equity packages, including a 401k
- Flexibility: Remote-first culture — work from anywhere
- Health: 100% Employer covered comprehensive health, dental, and vision insurance with a top tier plan for you and your dependents (US)
- Balance: Unlimited PTO policy
- Technical: AI First company; both Co-Founders are engineers at heart; and over 50% of the company is Engineering and Product
- Culture: Family-Friendly environment; Regular team events and offsites
- Development: Unparalleled learning and professional development opportunities
- Impact: Making the internet safer by protecting online transactions

## About Oscilar

## Company Overview
- **One-liner**: Oscilar provides an AI-native risk decisioning platform that uses agentic AI to help financial institutions manage fraud, credit, onboarding, and AML compliance in real time.
- **Entity Type**: Private (startup stage; funding rounds not publicly disclosed)
- **Headquarters**: Palo Alto, California, USA
- **Founded**: 2021
- **Founders**: Neha Narkhede (CEO) and Sachin Kulkarni (CTO)

## Core Business
- **Primary industry**: Financial technology (fintech) / Risk management / AI
- **Target customers**: Banks, fintechs, credit unions, and digital organizations (B2B, enterprise)
- **Mission**: “Making the internet a safer place for everyone” — empowering businesses to master risk, defeat fraud, and safeguard consumers in the era of AI.

## Products & Services
- **Oscilar AI Risk Decisioning Platform**: A unified, cloud-native platform that leverages agentic AI for detection, decisioning, and resolution across fraud, credit, AML, and onboarding. It processes over 30 billion decisions per year at peak throughput of 120,000+ requests per second with sub-100ms latency. Key components include:
  - **Agent Hub**: A coordinated suite of AI agents (e.g., Workflows, RuleRec, Credit Explainability, Analytics, TestGen, Fraud Disputes, AML L1, SAR, Narratives, Translator, Sanctions, PEP, CTR) trained on each customer’s SOPs and risk context. Agents define policies, score alerts, generate investigation narratives, and learn from analyst feedback.
  - **No-code policy engine**: Risk teams can define and deploy new policies in plain language without SQL or engineering support.
  - **Holistic risk dashboard**: Monitors the entire customer journey — onboarding, login, payments, compliance — in one place.
  - **Explainable decisions & full auditability**: Every decision is transparent and defensible for regulatory scrutiny.

## Market Standing
- **Valuation/Market Cap**: Not disclosed (private company)
- **Key Metric**: Processes 30B+ decisions per year; 120K+ requests per second; average latency <100ms. Employee count: ~104 (per Built In).
- **Notable Investors/Partners**: Not publicly listed from available sources. Advisors include Xin Ge (ex-CPO at Feedzai), Kevin Moss (ex-Chief Risk Officer at SoFi), Tomas Lobo (ex-Chief Technology & Risk Officer at Afterpay), and Rob Frohwein (co-founder of Kabbage, acquired by American Express).
- **Growth Signals**: Founded by Neha Narkhede (creator of Apache Kafka and co-founder of Confluent, NASDAQ: CFLT). Team built on deep risk experience from Meta, Uber, LinkedIn, Citi, and JPMorganChase. Currently hiring across multiple roles (33 jobs listed on Built In), indicating scaling. Remote-first culture supporting global talent acquisition.

## Competitive Advantages
- **Agentic AI tuned to customer data**: Models are trained on each institution’s own SOPs and risk patterns, retraining in days when patterns shift — not generic benchmarks.
- **Unified platform**: Covers fraud, credit, compliance, and AML in a single system, providing a holistic risk picture that competitors often address with siloed tools.
- **Low-latency, high-throughput architecture**: Proven at 120K+ req/s with sub-100ms latency, built by engineers who scaled 10-billion-requests-per-second systems at Meta.
- **Explainability & audit trails**: Full decision transparency for regulatory compliance, a critical differentiator for financial clients.
- **Feedback loop**: Analyst feedback continuously refines agent recommendations, improving over time.

## Strategic Focus
- **Deepen the Agent Hub**: Continue building and refining specialized AI agents for every risk decision type (fraud, AML, credit, sanctions, etc.).
- **Expand customer base**: Target more banks, fintechs, and digital organizations globally, with recent hires in sales and customer support (including Philippines office).
- **Maintain remote-first culture while scaling**: Leverage distributed talent to grow efficiently.
- **Invest in ML and generative AI**: Use cutting-edge tools to stay ahead of evolving fraud and compliance threats.

## Why Work Here
- **Remote-first culture**: Work from anywhere; company provides home office setup assistance.
- **Cutting-edge technology**: Opportunity to work on AI/ML at scale, tackling complex fraud and financial crime problems.
- **Elite team**: Collaborate with experts from Meta, Google, Uber, LinkedIn, Confluent, Citi, and JPMorganChase.
- **Values-driven**: Customer obsession, radical ownership, efficient growth, one team, bold vision with clear eyes.
- **Benefits**: Competitive salary and equity, unlimited PTO, comprehensive health/dental/vision insurance, regular team events and offsites, professional development opportunities.
- **Mission**: Direct impact on making the internet safer for legitimate customers and enabling financial institutions to grow confidently.

## Sources
1. [oscilar.com](https://oscilar.com) — Product overview, platform features, metrics
2. [oscilar.com/about-us](https://oscilar.com/about-us) — Leadership team, advisors, company origins
3. [oscilar.com/careers](https://oscilar.com/careers) — Culture, values, benefits, remote-first policy
4. [builtin.com](https://builtin.com/company/oscilar) — Employee count, year founded, job listings

## Other roles at Oscilar

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