Reports to VP Engineering.
Fliptop's customer intelligence platform uses data science to help companies close more sales. Our software seamlessly integrates with the most popular CRM and marketing automation systems, and models historical sales to predict how likely new leads will become paying customers. Our SpendScore has been used to prioritize sales pipelines, build prospecting lists, and optimize marketing campaigns.
We're well-funded (http://angel.co/fliptop), revenue-positive (seven-figures in 2013), and have a growing list of customers like Intuit and DataSift.
You will iterate and improve Fliptop's predictive modeling algorithms. You will work closely with engineers to productize and scale your work. You will effectively and succinctly explain Fliptop's data science to colleagues, customers, and investors.
Lead or Chief Scientist are on the table if you've got the right background.
- Advanced degree in Computer Science, Mathematics, Statistics or related field
- 3+ years experience in Natural Language Processing, Computational Linguistics, Machine-Learning - in industry or on a large-scale academic project
- Practical experience in a Linux environment
- Experience with one or more of the following programming languages: Scala, Java, Python, R
- Solid understanding of statistical methods: experimental design, analysis of variance / regression, logistic regression, non-parametric statistics
Good to have:
- Experience with Mahout and the Hadoop ecosystem
- Experience with BSP computing (Giraph, Hama, Pregel, etc.)
- Experience with NoSQL and graph databases
- Experience with streaming APIs
- Experience with Amazon Web Services
- Familiarity with existing NLP resources: Wordnet, POS taggers, parsers, LingPipe, SVMLight, NLTK, Weka, and similar tools.
What's in it for you:
- Competitive salary and early-stage stock options
- Fun office in SOMA with ping-pong and a loaded beer fridge
- Flexible work hours and telecommuting
- Open vacation policy
- Quarterly company volunteer activities (e.g. SF Food Bank, Glide, Exploratorium)
- Quarterly company fun activities (e.g. snowboarding, go-karting, sailing)