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SecurityScorecard is the global leader in cybersecurity ratings, continuously rating over 12 million companies across 64 countries. The company's patented technology is used by 25,000+ organizations for self-monitoring, third-party risk management, board reporting, and cyber insurance underwriting. Founded in 2013 and headquartered in NYC, SecurityScorecard has raised over $110M from world-class investors including Sequoia Capital, Silver Lake Waterman, Moody's, GV, and Riverwood Capital. The company has been recognized as one of the 10 hottest SaaS startups in New York for two consecutive years and named to Fast Company's World's Most Innovative Companies for 2023.
As a Senior Data Scientist, you will develop and implement advanced analytical models that drive insights and enhance the cybersecurity ratings platform. You will work on challenging problems spanning risk scoring, threat intelligence, and vendor risk assessment, collaborating with cross-functional product and engineering teams to integrate models into production systems.
Key responsibilities include building, evaluating, and deploying machine learning models; performing exploratory data analysis on large, complex datasets; validating model accuracy, robustness, and scalability; collaborating with product managers and engineers to define data science requirements; contributing to code reviews and design discussions; staying current on research and emerging technologies; and communicating findings to both technical and non-technical audiences.
Required qualifications: advanced degree in a quantitative field (Computer Science, Statistics, Mathematics) or equivalent professional experience; 5+ years applying data science and machine learning to real-world challenges; proficiency in Python and ML frameworks (scikit-learn, XGBoost, MLFlow, PyTorch); experience with cloud-based data pipelines (AWS, GCP, or similar); solid understanding of ML algorithms, evaluation metrics, and model deployment; strong communication and teamwork skills. Prior exposure to cybersecurity, threat intelligence, risk scoring, LLMs, or Scala is a plus.
