Stash is investing, simplified. We are an investing platform that makes it easy for anyone to start with as little as $5. Through empowering our users with education and guidance, we help investors learn the basics so they can do it themselves. At Stash, we are working toward a future where investors are as diverse as our world.
Stash is looking for a Data Scientist with a passion for building reliable, scalable, and performant software. We look for strategic thinkers and creative problem solvers with a bias for execution and we’ll expect you to contribute code as well as product/feature ideas from the get-go. If you are looking for a culture that encourages ownership, taking calculated risks, being data-driven and that values evidence over ego, this may be the role for you.
What you’ll do:
- You will work closely with our CTO and engineering teams to establish new systems for our products to predict and augment the Stash experience in ever more intelligent ways
- Design predictive models which grow and adapt as our products and customer base scale, utilizing machine learning, time-series and Bayesian statistics
- Work with large datasets to help us better understand our customers and anticipate their needs through distributed computation techniques
- Make rigorous statistical inferences from A/B testing on our product and customer segments
- Normalize our data across institutions and sources using semi-supervised learning
Who we’re looking for:
- MS in Computer Science, Statistics, Applied Mathematics, Physics, Engineering or a related field with 3+ years of experience
- 2+ years of professional programming work in Python, Scala, Java, or similar
- Experience with Pandas, R, or other statistical modeling frameworks
- An understanding of storing and querying data from Redshift, PostgreSQL, or similar
- Passion to use all aspects of data science, programming, and technology to build the financial advisor of the future
- Experience using machine learning to improve algorithmic systems
- Experience with machine learning frameworks such as Apache Spark or Apache Hadoop/MapReduce