Description

You will design and prototype scalable predictive models and analytics solutions using machine learning and optimization techniques.

Responsibilities

• Design, build, and implement predictive models using high-dimensional, real-time datasets.
• Develop machine learning and deep learning models for anomaly detection, including payment risk, membership abuse, and identity risk assessment.
• Run simulated and live experiments, such as A/B and multivariate tests, to drive KPI improvements.
• Build data visualizations and interactive dashboards to monitor and share business insights.
• Partner with product development teams to provide data-driven recommendations and insights.

Required Skills

• Advanced degree (Master or Ph.D.) in a STEM field.
• 5+ years of related experience in data science or analytics.
• Technical expertise in data mining, machine learning, and statistical analysis.
• Proficiency in Python and its machine learning/data mining packages.
• Programming experience in Java or JavaScript.
• Experience working on UNIX or Linux platforms.
• Experience working with large datasets and distributed computing tools.

Preferred Skills

• Experience building and deploying deep learning models in production.
• Experience in the fraud detection and abuse detection domain.
• Experience with BigQuery and GCP.

Key Skills

Education

Any Graduate