Data Scientist | Palo Alto, CA, United States
In the future, we believe that almost all new conversations will start through some device. This insight represents a profound understanding in how human-machine collaboration will change the human condition. It challenges us to look at the social context, mores and cues that enable conversations between people, who have never met, to take place with a familiarity occasioned between friends.
Your goal as a Data Scientist is to distill social meaning from the petabytes of data that are available at your fingertips. A key part of your love for data stems from your passion for social graphs, both from their structure and behavioral aspects. You know how to tell a story through data, but one that is statistically grounded, eschewing complexity and spurious correlations. You appreciate the difference between causation versus correlation, and with it an approach based on information theory. At the end of the day you do science, and this requires both empirical creativity as well as empirical inquiry.
We have multiple roles on our Data Science team. Your skills should be broad in nature however you should possess a passion for and strength in one of the following:
Social or Physical Science
Responsibilities depending on your area of strength could include:
Requirements if your strength is Machine Learning:
- you work with a fantastic data set: millions of people in social context, billions new log records every month
- focus on one of the company's top strategic priorities
- develop deep understanding and empathy for people who use our products
- many projects involve making predictions for how users will want to interact
- find data relationships using statistics, visualization tools, and social graph analysis
- create great recommendation algorithms, often relying on intuition mixed with clever feature selection
- work with machine learning experts to incorporate supervised and unsupervised algorithms
- design product changes and verify impact using measurements; you are responsible for experimental design and final interpretation of data
- participate in product development process, working closely with product managers and serving in the product management function when appropriate
- collaborate with engineering development teams to implement and upgrade algorithms
- help create tools, e.g., visualizations to glean new insights or ways to streamline routine activities
- share learnings internally and at conferences, collaborate with academic partners
- teach techniques, mentor, and inspire
- you will be studying people interacting with other people, which can be much more complex, interesting, and fun than studying people interacting with inanimate products, advertising, or other subjects of data science
- create great recommendation algorithms by combining intuition with clever choice of features and algorithms
- apply supervised and unsupervised techniques in context of large data sets and latent variables
- use graph algorithms to identify large-scale structure as well as local patterns
- deploy techniques for text classification and analysis
- collaborate with software engineers to implement production solutions, with models that work well at massive scale, and in real time
- collaborate with data scientists, including those who come from backgrounds in social science or other areas
Ph.D. in Computer Science with emphasis on machine learning. Alternatively, M.S. plus professional research-oriented machine learning experience.
5+ years working with the following languages and tools: Matlab, Octave, Python, C, C++, Java, Haskell...culminating in high proficiency
3+ years working with high-volume data, preferably with exposure to Hadoop ecosystem technologies
3+ years experience with SQL, strong abilities
excellent modeling skills, including ability to clearly define a problem in terms of objectives, constraints and assumptions
previously worked with a great variety of challenging data sets,
steering clear of overfitting risks and delivering practical solutions
practical experience deploying a wide variety of machine learning
techniques, ability to identify advantages and limitations for each
Requirements if your strength is Social or Physical Science:
Ph.D. in social science, physical science, or life science field. Alternatively, M.S. plus research-oriented professional experience.
5+ years working with R, Matlab, Python, or other tools, culminating in high proficiency
3+ years experience with SQL, strong abilities.
considerable experience with (personally, professionally, or academically) social networking or social discovery
extensive experience interpreting, understanding, and modeling data. In total, thousands of hours and hundreds of data sets.
insatiable curiosity about understanding social interactions, especially in an online context
rigorous approach to statistics, data quality, and experimental design
excellent modeling skills, including ability to clearly define a problem in terms of objective, constraints, and assumptions
ability to tell a story through data, for your own understanding, for other data scientists, and for colleagues, including those with limited domain expertise