Senior Data Scientist
Senior Data Scientist:
When was the last time you were planning a business trip and really tried to save your company money? If your company allowed you to stay in a fancy hotel, would you ever volunteer to stay at an Airbnb or at a friend's house? How about flying coach instead of business class? The vast majority of employees optimize for comfort and convenience, spending at the high end of their company policy limits, because, well, why not? So how can a company get its employees to care about expenses without implementing draconian policies, creating friction and frustrating employees? How can a company motivate its employees to save?
The answer is Rocketrip. We're a NYC-based startup that rewards business travelers for cost-sensitive behavior. It's a win-win: companies save, while employees cash in with real rewards.
The Role:
At Rocketrip, our most important asset is our data. Our Data Science Team helps drive engagement with the platform through deep data analysis of use and travel industry data. We work with large sums of data and we’re looking for data scientists who can help define how we should be leveraging this information to drive our product roadmap strategy. You will work with analysts, product managers, engineers, and senior leaders to design well-constructed analyses and deliver actionable results.
What You’ll Do:
- Enhance our machine learning models with the latest in machine learning algorithms
- Design and implement production data pipelines
- Formulate experiments and conduct hypothesis testing
- Independently collaborate with engineers, business stakeholders, and the data team to help make decisions based off of data.
- Manage end-to-end projects, from the conceptualization of a business problem to prototype to deployment and monitoring
You Should Have:
- 3+ years of experience in self-managing an entire data science project in a production environment
- Strong ML, Stats, and Software Engineering fundamentals
- The basics: Python, Bash, Sklearn, Scipy, Pandas, SQL, familiarity with AWS suite, and the ability to write APIs
- Experience in understanding a business problem, identifying a solution, communicating it, and then implementing it
- The ability to operate outside of the framework of mainstream ML packages, i.e. the ability take a concept from white paper and implement it in production.