Data Scientist

Compensation: $160K-$200K base + bonus

Location: Hybrid onsite 4 days in West Hollywood or Valencia

Client: Financial

Data Scientist – Fraud Team

Reports To:

Chief Technology Officer

Position Summary:

Looking for a well-rounded individual with a strong background in data analysis, data handling, and Machine Learning algorithms. This individual will have effective communication skills and be able to participate in customer meetings.

Technical Skills:

• Proficiency in programming languages such as Python or R.
• Experience with machine learning frameworks and tools.
• Strong SQL skills for data extraction and manipulation.
• Experience with distributed computing frameworks for handling large data volumes.
• Amazon Web Service (AWS) platform experience would be a plus.

Responsibilities:

Data Analysis and Exploration:

• Conduct in-depth analysis of large-scale datasets to identify patterns and anomalies associated with fraudulent activities.
• Collaborate with teams to understand business requirements and design data-driven solutions.
• Research and incorporate external fraud intelligence feeds, identity data, and other third-party data sources to bolster capabilities.

Machine Learning Model Development:

• Develop and implement machine learning models for fraud detection and prevention.
• Continuously optimize and enhance existing models to improve accuracy and efficiency.
• Conduct controlled A/B testing and experimentation to compare efficacy of models and approaches

Data Management:

• Define and manage end-to-end data processes, ensuring data quality, integrity, and security.
• Collaborate with IT and security teams to establish robust data governance practices.
• Implement robust model management practices including versioning, monitoring, and retraining.
• Ensure compliance to relevant regulations (e.g. PCI-DSS) and data privacy laws.

Threat Hunting:

• Build, foster, and maintain relationships within the fraud detection and threat hunting ecosystem in service of ensuring that the latest tools and techniques are incorporated into the platform.
• Creation and selection of methodologies specific to fraud detection and threat hunting, such as behavioral fingerprints, velocity checks, and risk scores

Collaboration and Communication:

• Familiarity with BI and visualization tools to facilitate the creation of dashboards and reporting mechanisms.
• Work closely with stakeholders to understand their needs and translate them into actionable insights.
• Present findings and recommendations to both technical and non-technical audiences.
• Ability to effectively participate and communicate in customer meetings.

Innovation and Research:

• Stay abreast of the latest advancements in data science, machine learning, and fraud detection technologies.
• Proactively explore and recommend innovative solutions to enhance fraud detection capabilities.

Requirements:

Educational Background:

Advanced degree in Data Science, Machine Learning, Statistics, or a related field or equivalent industry experience.

Experience:

• 5+ years of experience in developing and deploying machine learning models for fraud detection.
• Proven track record of successfully managing end-to-end data processes.

Communication and Collaboration:

• Excellent communication skills with the ability to convey complex technical concepts to non-technical stakeholders.
• Proven ability to work collaboratively in cross-functional teams.

Security Awareness:

Understanding of cybersecurity principles and best practices.

How to Apply:

APPLY