At Falkon, we're building a new system of intelligence that empowers professionals to define, understand and improve metrics that really matter.
We are product, engineering and research veterans from Microsoft, Amazon, Dropbox, Amperity, and Zulily. Having lived through years of bad metrics meetings and fire-drills, we've discovered a revolutionary way to combine machine learning and human intuition to empower professionals to define, understand and improve metrics that really matter.
We are looking for our founding data scientist, who will define the statistical and data science foundation for our core product and work with our machine learning team to build, deploy and maintain models working against massive customer datasets. As an early and critical member of our growing team you will help shape our technology, business, processes and culture.
What you will do
- Combine unsupervised and supervised learning with human expertise to go far beyond today's "best of breed" solutions.
- Experiment and deploy new models and algorithms to identify trends and optimize for signal/noise ratio in metrics data
- Build high-performance algorithms that can process data streams with billions of points of data every second.
- Design and implement novel techniques to extract meaning from the relationships inherent in metrics data.
- Help shape Falkon's culture, and build the workplace of your dreams
What you will need to succeed
- Alignment on Falkon principles - Think big, Deliver results with urgency, Be radically transparent, Follow the golden rule, Get better every day
- Ability to operate with autonomy in highly ambiguous situations
- Deep experience in building statistical and machine learning models to detect anomalies and extract trends from metrics data - preferably at high volumes in production.
- Ability to unblock yourself in terms of data import, data prep, feature engineering and model evaluation
- Ability to deploy the right tools for the task - i.e. not trying to build an ML model when a well-understood statistical technique would be a better fit.
- Ability to understand the business problems we’re trying to solve with our technology
- Strong math and statistical skills
- A PhD in Statistics or Mathematics with solid computer science fundamentals preferred.
- 75% data science skills and 25% software engineering skills
- Experience working with machine learning engineers on machine learning pipelines
If you're interested in rapid career growth, there is no better place to be than Falkon.
Growth comes from Impact x Learning
At Falkon you'll do your best work, develop new skills, learn from the best, discover what technical areas you're truly passionate about and help our customers grow their businesses. You'll also get the opportunity to see how a venture-funded business is built from the ground up.