Data Scientist

Compunnel, Inc.; Sunnyvale (CA); On-site; USD 100,000 - 140,000; Full time

Job summary

A prominent tech firm in Sunnyvale is seeking a highly skilled Data Scientist to design and implement predictive models for fraud detection and abuse. The ideal candidate will excel in data storytelling and have a strong technical background in machine learning, specifically in production environments. Responsibilities include building models, visualizing data insights, and contributing to research initiatives. Candidates should hold a relevant degree and possess experience with large datasets.

Qualifications

• Expertise in machine learning and data mining techniques.
• Proficiency in Python and relevant packages.
• Experience with large datasets and distributed computing tools.

Responsibilities

• Design and build predictive models for fraud detection.
• Communicate insights via data visualization.
• Build dashboards for stakeholders.

Skills

Machine Learning

Data Storytelling

Statistical Analysis

Python

Anomaly Detection

Education

Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field

Tools

GCP

BigQuery

Job description

We are seeking a highly skilled Data Scientist to design and implement predictive models using high-dimensional, real-time datasets.

The ideal candidate will apply advanced machine learning and data mining techniques to detect fraud and abuse, support strategic decision-making, and contribute to innovation through research and patent filings.

This role requires strong technical expertise, storytelling with data, and experience in production environments.

Key Responsibilities

• Design, build, and deploy predictive models for fraud and abuse detection, including account takeover (ATO), membership fraud, trial abuse, LTO abuse, and bot attacks.
• Own fraud/abuse risks for specific products or segments and act as a strategic partner to product development teams.
• Communicate insights and recommendations effectively through data storytelling and visualization.
• Build interactive dashboards and visualizations for internal and external stakeholders.
• Apply ML/AI, deep learning, and data mining techniques to develop robust anomaly detection models.
• Contribute to research initiatives and US patent filings to address emerging fraud issues and automate processes.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, or a related field.
• Strong technical expertise in machine learning, statistical analysis, and data storytelling.
• Proficiency in Python and machine learning/data mining packages.
• Experience working with large datasets and distributed computing tools (GCP/BigQuery preferred).
• Experience with production deployment of models.
• Familiarity with GenAI and Agentic AI technologies.

Preferred Qualifications

• Experience in fraud detection or anomaly detection domains.
• Knowledge of cloud-native tools and services for scalable model deployment.
• Experience in patent filing or research-driven innovation.