Oscilar, Inc
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.
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 Analyst at Oscilar, you will be a trusted partner to our customers and will be responsible for providing the analytics, insights and recommendations to protect their business from fraudulent activities. As an early member of the product analytics team you will have great impact in building and scaling our managed services business. Responsibilities:
Fraud & AML Analytics
Analyze large-scale transaction, account, and behavioral datasets to identify
fraud, AML, and abuse patterns
across: Onboarding
(synthetic identity, fake accounts, mule risk)
Account activity
(ATO, session hijacking, social engineering)
Payments
(card-not-present fraud, ACH/wire fraud, crypto typologies)
Develop
risk segmentation, cohorts, and KPIs
(fraud rate, approval rate, loss rate, false positives).
Evaluate rule-based and ML-driven decision strategies and quantify
performance trade-offs .
Customer Risk Strategy & Enablement
Partner with customers to: Diagnose their fraud and AML pain points
Interpret model outputs, alerts, and decision logic
Design and refine
risk strategies
using our platform
Produce
customer-facing analytics , dashboards, and readouts that translate data into
actionable risk decisions .
Act as a trusted analytics advisor for customers implementing or scaling fraud programs.
Product Collaboration
Work closely with Product and Engineering to: Define data requirements and success metrics for new features
Provide feedback on model explainability, rule tooling, and case workflows
Identify gaps in data, signals, or product capabilities based on real customer usage
Support experimentation (A/B tests, challenger strategies, rule tuning).
Thought Leadership & Documentation
Contribute to internal and external documentation, including: Fraud and AML best practices
Lifecycle risk frameworks
Playbooks for onboarding, ATO, and payment fraud
Help shape standardized analytics and reporting frameworks across customers.
Requirements:
4+ years of experience as a data analyst, data scientist or a related field, with a focus on fraud prevention and/or anti-money laundering.
Proficiency in Python and SQL.
Knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection.
Experience working with large datasets and 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.
What Success Looks Like:
Customers use your insights to
materially improve fraud loss, approval rates, or operational efficiency .
Product teams rely on your analyses to
prioritize features and data investments .
You help establish our platform as a
trusted risk partner , not just a tooling provider.
Why Join Us:
Work on cutting-edge fraud and AML challenges across fintech, payments, and crypto.
High visibility role influencing
product strategy and customer outcomes .
Opportunity to shape how modern risk teams operate at scale.
Benefits
Compensation : Competitive salary and equity packages, including a 401k
Flexibility : Remote-first culture — work from anywhere
Health : 100% Employer covered 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
#J-18808-Ljbffr
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 Analyst at Oscilar, you will be a trusted partner to our customers and will be responsible for providing the analytics, insights and recommendations to protect their business from fraudulent activities. As an early member of the product analytics team you will have great impact in building and scaling our managed services business. Responsibilities:
Fraud & AML Analytics
Analyze large-scale transaction, account, and behavioral datasets to identify
fraud, AML, and abuse patterns
across: Onboarding
(synthetic identity, fake accounts, mule risk)
Account activity
(ATO, session hijacking, social engineering)
Payments
(card-not-present fraud, ACH/wire fraud, crypto typologies)
Develop
risk segmentation, cohorts, and KPIs
(fraud rate, approval rate, loss rate, false positives).
Evaluate rule-based and ML-driven decision strategies and quantify
performance trade-offs .
Customer Risk Strategy & Enablement
Partner with customers to: Diagnose their fraud and AML pain points
Interpret model outputs, alerts, and decision logic
Design and refine
risk strategies
using our platform
Produce
customer-facing analytics , dashboards, and readouts that translate data into
actionable risk decisions .
Act as a trusted analytics advisor for customers implementing or scaling fraud programs.
Product Collaboration
Work closely with Product and Engineering to: Define data requirements and success metrics for new features
Provide feedback on model explainability, rule tooling, and case workflows
Identify gaps in data, signals, or product capabilities based on real customer usage
Support experimentation (A/B tests, challenger strategies, rule tuning).
Thought Leadership & Documentation
Contribute to internal and external documentation, including: Fraud and AML best practices
Lifecycle risk frameworks
Playbooks for onboarding, ATO, and payment fraud
Help shape standardized analytics and reporting frameworks across customers.
Requirements:
4+ years of experience as a data analyst, data scientist or a related field, with a focus on fraud prevention and/or anti-money laundering.
Proficiency in Python and SQL.
Knowledge of machine learning algorithms and statistical techniques, with a focus on their application in fraud detection.
Experience working with large datasets and 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.
What Success Looks Like:
Customers use your insights to
materially improve fraud loss, approval rates, or operational efficiency .
Product teams rely on your analyses to
prioritize features and data investments .
You help establish our platform as a
trusted risk partner , not just a tooling provider.
Why Join Us:
Work on cutting-edge fraud and AML challenges across fintech, payments, and crypto.
High visibility role influencing
product strategy and customer outcomes .
Opportunity to shape how modern risk teams operate at scale.
Benefits
Compensation : Competitive salary and equity packages, including a 401k
Flexibility : Remote-first culture — work from anywhere
Health : 100% Employer covered 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
#J-18808-Ljbffr