Data Scientist
Location: US, CA, San Francisco
Department: Engineering
Employment type: Full-time
Required education: Bachelor's Degree
Function: Engineering
Company profile: Premise is building a novel information-gathering network on a global scale. The network harnesses the explosion in mobile technology, combined with sophisticated machine learning capabilities, to aggregate observations from users all around the world to deliver business, economic and human development data in real-time. We are growing the platform to sufficient scale where it will deliver any user-observable information on demand, whether that is the price of food staples at a Mumbai street market, or the length of a queue at a Walmart de México parking lot.We’re a fast-growing startup -- bolstered by the backing of significant ‘smart money,’ but still young enough such that you’ll be a core member of the team that is reinventing how the human race understands its own economic activity. We’re being helped in our mission by Silicon Valley’s most creative and disruptive investors: Social+Capital Partnership, Google Ventures, Andreessen Horowitz and Harrison Metal.Bottom line, this is an opportunity for someone who (1) wants to build something meaningful at a fast-growing and mission-driven startup, (2) wants to contribute to the amazing, messy evolution of the open-source ecosystem, and (3) actually cares about social good enough to make Premise a permanent part of their resume.Read more about Premise * TechCrunch: #URL_381f76dfce96ab77e6fe5181ebb500e6c1bcba003861c737f3c721b47d9a2b17# * New York Times:#URL_faf9a8fdc4802642fd81e7b36325164b67f939328bd86c959018f1db1d4ec784#?hpw&rref=business&_r=1& * Wired: #URL_b80f608b08c2ba4ae61aa641ed4d73de557d09c00692ceba27a5cf8c44a6bf96# * The New Yorker:#URL_42671b5464823a632cd07ad33ae34c9d33d88a4f36aefcb6aadc87e40f9b6e16# * The Atlantic:#URL_ff8989377bd24ee8d51289196a427f4ddcbebccf08409ba4f2944721192e671d# * MIT Technology Review:#URL_78f5a144ee0c4e1f2fa86473817f5623350989c3c7d0493d5e71157aa5f7380d#
Description: ResponsibilitiesResearch and propose quantitative methodologies to solve business and engineering problems, focusing on anomaly detection, supply-demand matching / sampling design, gamification, and automated quality controlPropose solutions and find answers to questions ranging from understanding user behavior, identifying fraud and sampling design anomalies, building quality & trust models, and finding budget allocation inefficiencies.Develop novel algorithms for time-series analysis, dimensionality-reduction and media signal analysis.
Requirements: Required QualificationsStrong quantitative background: BS, MS or PhD in Computer Science, Statistics, or Operations Research.1+ years of experience in performing analysis using one or more of Python, SQL and R.Keen sense of both "where to look next" and "what to do instead", when performing open-ended statistical analysis, retaining mathematical rigor.Navigate open-ended areas with a strategic mindset.Sustained attention to quality & detail, self-starter & excellent communication skills, programming chops.Bonus QualificationsPrior startup experience (preferably in an analysis-oriented engineering or product role) in developing new productsExperience with machine-learning models for clickstream, geospatial, text / sentiment analysis, as well as optimization techniques.Passion for creating products; personal projects or other work (send us links to your GitHub repos)Experience with handling large datasets
Fraudulent: 0