Information Research Scientists (San Francisco)

San Francisco, CA /
Analytics /
About CyberCube:

1) The market leader in digital analytics with the mission of delivering the world’s leading cyber risk analytics on one of the most critical risks of today and the future.
2) Hypergrowth startup that has raised over $50mm in capital from top tier VCs.
3) Explosive team growth (from 15 employees in SF to 100+people globally and growing 50% more in 2021).
4) Explosive client base growth path having tripled our clients in 2020.
5) Phenomenal company culture where we are committed to enabling you to do the best work of your career. Check out our perfect score on Glassdoor!
6) An incredible high performing team of insurance industry professionals, data scientists, and engineers who love working here.
7) CyberCube and its products win industry awards every year (eg. CyberRisk Solution of the Year 2021).
8) Openness and accessibility of senior leadership including heads of Functions and CEO.

Design and build new analytical data models and develop theories to improve existing technology and solve complex problems with risk analytics software.  May perform additional duties that are similar and consistent with stated position
Qualified candidates must possess a Master’s degree in Computer Science, Information Science, Mathematics, Statistics, or closely related field plus 1 year of experience.  Employer will accept experience gained during university studies.  Of the required experience, must have 1 year of experience in each of the following:


    • Distributed processing using all of the following technologies: Map Reduce, Spark, Amazon Web Services (AWS)
    • Advanced Statistical Methods including Multivariate analysis, Time-series Analysis, Supervised Machine Learning (including Linear Regression, Logistic Regression, Decision Trees, and Ensemble Learning), Unsupervised Machine Learning (including Clustering), Dimensional Reduction (including Principal Component Analysis), and Anomaly Detection
    • Data Visualization using Matplotlib, Plotly, Seaborn, and TensorBoard for exploratory analysis and interpretation of high-dimensional vector representations of data, for performance monitoring of machine learning models, and for monitoring data distributions over time  
    • Python and Jupyter reporting using all the following Machine Learning libraries: Pandas, NumPy, SciPy, scikit-learn, and TensorFlow
Send resume to or
CyberCube Analytics, Inc.
58 Maiden Lane, 3rd Floor
San Francisco, CA 94108

CyberCube Analytics, Inc. is an equal opportunity employer. We don’t tolerate discrimination against age, gender, gender identity, gender expression, sexual orientation, race, color, nationality, ethnicity, religion, disability, veteran status, protected genetic information or political affiliation.