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Job Code: #10733
Title: Data Scientist
Job Location: Lehi, Utah

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Job Description:

PDS is in need of a Data Scientist:

What We Are Looking For…

Our client is building a Big Data Platform to bring real time and batch analytics to the small business marketplace.  This position will work closely with our Big Data Engineering group to explore data and develop Machine Learning algorithms that will help to our customers to make better, more informed decisions.  This is a very exciting opportunity to explore new technologies and build the future of data at Infusionsoft from the ground up.

Your Big Three Ways You’ll Help Small Businesses Succeed:

  1. Find meaning in the data we collect about small business.
  2. Work closely with Big Data Engineers to discover Machine Learning algorithms that can help our customers make better decisions.
  3. Help to identify and capture new data that can drive business success even further.

What Will Our Big Data Engineer Look Like?

Who you are:

  • Highly organized, logical thinker that is driven to find meaning in data and to share that meaning with others
  • Thrives in a collaborative environment. Works closely with business analysts and technical personal to answer questions.

Who you are not:

  • More concerned with perfecting the algorithm than using it provide value

Daily Deeds

  • Work closely with small business experts to derive the questions that need to be asked
  • Exploring the data that we have to answer those questions
  • Working closely with Big Data Engineers to implement the algorithms
  • Suggesting new data that we can capture to enhance our capacity to provide meaningful insights

Gotta Have…

  • Strong Analytical Experience
  • Strong background with Machine Learning
  • R, MatLab or Octave

Ideally, You Will Possess…

  • Java / Scala / Python experience
  • Spark Experience
  • Familiarity Hadoop or Cassandra

Challenges You Can Help Us Face (with optimism)

  • How do we provide useful business insights to help small business succeed?
  • How do we establish ourselves as a contributor / respected participant in the Big Data Community?
  • How do we ensure stability and fault tolerance as we continue to scale?

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