Role:Data Scientist

Location:San Francisco, CA

• As the Data Scientist, youâ??ll be responsible for developing and testing hypotheses on behavioral responses in B2B marketing, creating models that extract data from, among others, website, digital advertising, and CRM solutions into actionable insights, and defining leading edge thinking on how analytical frameworks can be applied to predictive marketing.
  
• We deal with a large number of known problems with NLP such as relation extraction, NER, cross-document summarization, natural language generation, topic modeling, entity linking/disambiguation, large-scale machine learning over graphs, to problems novel to this domain such as personalized ranking of information, predicting the quality of relationships, etc.
• You will be both hands-on and strategicâ??with both a broad ecosystem-level understanding of our market space and working as part of the engineering and product teams to deliver software in an iterative, continual-release environment.
• This is a high-visibility position involving close collaboration across functional groups and with executive stakeholders at customers like the above.
  

Why you want to join us:

• Be part of an experienced team in Natural Language Understanding, Graph, Deep Learning, and Enterprise Applications with intimate knowledge of the domain
  
• Help us to introduce mainstream NLU into Enterprise Applications
  
• Collaborate on engineering real-time APIs and customer-facing Applications at the cutting edge where business technology meets artificial intelligence.
  
• You would have access to a unique set of data capturing all interactions between businesses, which is sought after by many researchers.
  
• We are uniquely positioned with significant Intellectual Property
  

Responsibilities:

Define: Work with customers and internal stakeholders to define hypotheses and models. We are dealing with all aspects of Business-to-Business sales and marketing problems and first to apply data science to them.

Document: Write clear, concise descriptions of how insights can be converted into repeatable actions.

Test: Continually iterate your models and refine assumptions, data sources and more.

Code: Build out new applications and business solutions as part of a combined data scientist / machine learning / engineering team

Communicate: Drive understanding and buy-in among all stakeholders at all levels.

Requirements:

• PhD or Masters Computer Science, Math, Statistics Computational Mathematics
  
• Strong background in algorithms and dealing with large-scale data problems
  
• Experience with Scala, Spark or Hadoop or other large-scale data processing platforms
  
• Experience with SQL or NoSQL databases
  
• Experience in taking a large or enterprise application into production
  
• Proven ability to solve problems using state of the art technology
  
• Proven ability to innovate when necessary, but not reinvent the wheel
  
• Intuition and experience with NLP/IR or graph data is a plus
  
• Proven ability to apply machine learning to a wide range of problems
  

Skills:

• Imagination beyond what has been done before
  
• Experimental yet pragmatic ablility to create something useful
  
• Flexibility to deal with ambiguity in requirements
  
• Hands on, and not afraid to wear multiple hats
  
• Passion for career growth and development into a leadership position
  
• Ability to provide technical guidance and leadership to other engineers