Senior Data Scientist
Goodwater CapitalWe help entrepreneurs build companies that transform lives around the world.
Posted 3 months ago
We are looking for data scientists who love exploring data and uncovering insights to help shape the future of venture investing. Our team is creating innovative data-driven solutions that are impacting critical business decisions for Goodwater and our portfolio companies.
Do these qualities describe you?
Curiosity: You notice patterns and phenomena and ask “why?” You’re hungry to learn the broader context and consequences of your work.
Quantitative and qualitative thinking: You seek out the best available data and explore it to answer “why?” Your analyses and insights are guided and vetted by your qualitative understanding of consumer behavior and market trends.
Humble and collaborative: You have come to realize that the more knowledge you gain, the less you actually know, and that pushes you to continually seek knowledge from others. You are also eager to share your knowledge and insights with others.
Entrepreneurial: You’re comfortable with moving fast and adapting to fluid roadmaps and priorities. You aren’t afraid of failure and look for creative solutions to overcome challenges.
If this sounds like you, here are some qualifications we’re looking for:
- 4+ years of industry experience
- Experience analyzing product, user, and/or business data for tech companies
- Ability to translate open-ended business questions into concrete data analyses
- Experience identifying trends, patterns, and anomalies from large and disparate data sets
- Ability to interpret and present analytical insights to stakeholders
- Knowledge of statistics and experience building statistical models
- Experience implementing machine learning models using TensorFlow, scikit-learn, or other libraries
- Proficiency in Python, R, or other data analysis tools
- Fluency in SQL
- Experience evaluating investment opportunities, for example at a bank, VC firm, or hedge fund
- Experience improving time-series models in production environments