Fraud Data Science at Vana

Argentina

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Not SpecifiedCompensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Fintech, Banking, InsuranceIndustries

Requirements

Degree in Data Science, Statistics, Mathematics, Computer Science or a related field with strong programming skills [MUST]
1-2 years of experience in Data Science, Data/Business Analytics (with ML knowledge) [MUST]
2+ years of Python and SQL experience [MUST]
Knowledge of fraud detection, anomaly detection, or modeling with imbalanced datasets [MUST]
Strong analytical skills and a problem-solving mindset, with the ability to extract actionable insights from data [MUST]
Industry background in fintech, insurance, or banking is valued but not required [DESIRABLE]
AWS Services knowledge is a Plus [DESIRABLE]
Understanding of consumer behavior, alternative data sources, and digital lending platforms [DESIRABLE]

Responsibilities

Data analysis and modeling: Explore large-scale transactional and behavioral datasets to uncover patterns associated with fraud
Model development and validation: Build and validate classification models using ML techniques tailored to imbalanced problems (fraud vs. non-fraud)
Feature engineering: Create derived variables that enhance model performance and generalization while avoiding overfitting
Cross-functional collaboration: Work with engineering, product, and operations teams to ensure seamless integration of models into decision flows
Monitoring and iteration: Track model performance in production and iterate based on behavioral changes, fraud trends, or strategy shifts
Research and innovation: Stay up to date on cutting-edge ML techniques for fraud detection in digital transactional environments

Skills

Key technologies and capabilities for this role

Machine LearningSupervised LearningUnsupervised LearningFeature EngineeringImbalanced ClassificationData AnalysisModel ValidationFraud DetectionPythonSQL

Questions & Answers

Common questions about this position

What experience and skills are required for the Fraud Data Science role?

Candidates must have a degree in Data Science, Statistics, Mathematics, Computer Science or related field, 1-2 years in Data Science or Analytics with ML knowledge, 2+ years in Python and SQL, knowledge of fraud detection or imbalanced datasets, and strong analytical and problem-solving skills.

Is prior experience in fintech or banking required?

Industry background in fintech, insurance, or banking is valued but not required.

What is the salary or compensation for this position?

This information is not specified in the job description.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What makes a strong candidate for this Fraud Data Science role?

A strong candidate will have the must-have requirements like Python/SQL experience, ML knowledge for imbalanced datasets, and fraud detection skills, plus desirable experience in fintech/banking, AWS, and understanding of consumer behavior in digital lending.

Vana

Decentralized platform for personal data management

About Vana

Vana operates a decentralized platform that allows individuals to manage and monetize their personal data. Users can control what information they share, with whom, and how much they earn from it. This platform is designed for those who are aware of their digital footprint and want to benefit from their data, including tech-savvy individuals and privacy advocates. Vana differentiates itself by creating an open ecosystem where users can own their digital identities and engage in transactions with data buyers, earning money in the process. The company's goal is to promote a more equitable data economy, ensuring that individuals are rewarded for their personal data while fostering a community where users can thrive.

San Francisco, CaliforniaHeadquarters

2021Year Founded

$24.3MTotal Funding

EARLY_VCCompany Stage

Data & Analytics, Crypto & Web3Industries

11-50Employees

Benefits

Competitive base salary

Health insurance, dental and vision

Flexible work schedule

Unlimited PTO

Risks

Emerging competition from platforms like Ocean Protocol could dilute Vana's market share.

Regulatory scrutiny on data privacy may impose additional compliance costs for Vana.

Volatility in cryptocurrency markets poses financial risks to Vana's transaction values.

Differentiation

Vana empowers users to monetize their data through decentralized autonomous organizations (DAOs).

The platform offers data portability, allowing users to control data across multiple services.

Vana's community-focused approach rewards users for contributing data, enhancing user engagement.

Upsides

Vana secured $200M in funding, indicating strong investor confidence in its model.

The rise of DataDAOs creates new opportunities for user engagement and monetization.

Growing interest in data privacy boosts demand for Vana's decentralized data management solutions.

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