Data Science, VP
New York, NY /
Research & Development /
You’re a self-starter. You believe in tackling the most important problems, even if they are the most difficult problems. You’re comfortable with the unknown and understand that #startuplife means that you’re going to be wearing multiple hats. And that’s what motivates you. You’re accountable and obsessed with improvement, both in yourself and in others. You’re up to the challenge of building a world-class company that aims to be the infrastructure for more secure software for all.
About the Company:
CertiK leads blockchain security by securing smart contracts and blockchains with cutting-edge Formal Verification technology. Founded by Computer Science professors of Yale University and Columbia University, CertiK has audited and secured over $5B in assets, including many of the world’s top blockchain projects.
The research efforts of CertiK have received grants from IBM and the Ethereum Foundation, and notable blockchain investors include Binance Labs, Bitmain, Lightspeed Venture Partners, Matrix Partners, and NEO Global Capital, among others.
- Serve as a lead in data science and analytics to frame competitive market strategies
- Lead a statistical data-driven approach to evaluate and prioritize integration opportunities that drive the highest impact in blockchain auditing service using statistical data analysis and coding skills
- Create computational linear regression models for time-series analysis;
- Develop automated design approaches to conduct statistical hypothesis tests including T/Bonferroni/Anova/Chi-Squared Tests, validate findings to identify key factors and analyze current market trends and demand
- Provide management with consultative services such as competitive data analysis, sales data management, integration activities, data and system interconnectivity and design
- Supervise the technical development and implementation of dashboard solutions in support of business objectives and advanced recurring automated reports
- Bachelor's degree in Statistics, Mathematics or a related quantitative field. Advanced statistical knowledge of multiple linear regression, categorical data analysis, logistic regression, linear and non-linear dimensionality reduction methods
- Strong skills in data/time series analysis, working/solving problems with data and building advanced analytical models
- Proficient in R, SQL, VBA