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 Analyst with a passion for building reliable, scalable, and performant software. The volume of our data is reaching an inflection point in its growth. You will work with a team of driven and smart data scientists to bring the voice of our customer to life from their behavioral and financial data. We work on models and insights which promote healthy investing and savings habits for our customers. 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:

• Automate data processes getting information to decision makers efficiently
• Build large scale data pipelines and frameworks for optimization supporting product, finance, and marketing teams within Stash
• Advise business teams on testing processes and statistical frameworks that allow our teams to iterate and evolve at high speeds
• Work with large datasets to help us better understand our customers and anticipate their needs through distributed computation techniques
• Analyze and provide insights that improve core KPIs or client experience using data
• Monitor data processes, providing the support that teams rely on to make decisions on a daily basis

Who we’re looking for:

• BS in Computer Science, Statistics, Applied Mathematics, Physics, Engineering or a related field with 2+ years of experience
• Passion for learning, iterating and challenging ideas from a mathematical perspective
• Strong experience in machine learning techniques, with preferably some exposure to deep learning
• Python and Pandas familiarity preferred (1-year experience required )
• Experience with distributed data systems such as Spark
• 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
• Ability to reduce complicated problems into more simple ideas and communicate those clearly to key stakeholders

**No Recruiters, please