Lead Data Scientist
Engineering & Product
Tesorio has created a platform to help the Fortune 5,000,000 run as if they had a Fortune 500 finance team. We plug into a company’s data sources about cash in/out and our job is to leverage data science to surface the most impactful actions they can take to optimize their cash flow—and let them implement those actions with the click of a button.
Our clients are empowered to share their best practices and share their bucket list of info they’d like at their fingertips. We’re looking for talented engineers to help us implement a high volume of curated ideas and reinvent how complex financial transactions can be simplified to the click of a button.
We are developing machine learning algorithms to understand business cash needs, predictive algorithms to forecast future cash flow, and a sleek UI/UX to make our products enjoyable to work with. You’ll be joining an early-stage company with a small, tight-knit team, backed by top-tier VCs (including First Round, Floodgate, Fuel and Y Combinator). You’ll work closely with the entire engineering team and the co-founders. Learn more at tesorio.com.
- You have a PhD in a quantitative discipline and/or years of experience as a data scientist
- You have deep expertise in applied statistics and/or machine learning
- You’re proficient in Python, R and/or SQL
What you’ll do day-to-day
- Work directly with the founders and engineers to build predictive models
- Discover trends in how companies are growing and understand their financial situation
- Analyze large company financial data sets
The ideal candidate
- Has 5+ years of work experience
- Is resourceful and a fast learner
- Excited to be working in a fast-paced environment with a small and talented team
- Experience in large-scale, data-rich environments
Nice to have
- Experience working with any of: Spark, Jupyter, Redshift/Hive, Athena/Presto, GPUs/TPUs, deep learning
- Experience with setting up and deploying machine learning models in the cloud
Note: we currently cannot sponsor visas.