Machine Learning Analyst

The Role

This position plays a key role working with customers to align strategic goals and objectives with key decisions regarding Machine Learning, Analytics and Salesforce.com related solutions. Must be able to manage and deliver components of customer engagements that include analysis and implementation of optimized machine learning technologies.  A candidate should have experience designing creative solutions that help clients maximize the power of their data to uncover new insights and reach new levels of automation. 

Education & Skills Required

  • M.S. or B.S. degree in Computer Science, Software Engineering, Statistics, Mathematics or equivalent combination of relevant work experience and education
  • 1-2 years experience working with data and technology platforms that combine the following experience:
  • Machine Learning, Data Warehousing or Big Data consulting 
  • Strong analytical skills with a thorough understanding of how to interpret customer business needs.
  • Experience with enterprise technology systems and large data sets
  • Strong expertise in at least two the following areas is required:
  • R, Python, SQL, Java
  • AWS, Azure, TensorFlow, Google Cloud AI
  • Salesforce.com solutions, including Einstein 
  • Implementation of BI or Data Management solutions
  • Experience implementing solutions for the Consumer Goods industry
  • Experience implementing solutions for the High Tech Manufacturing industry
  • Enthusiastic, professional and confident team player with a strong focus on customer success who can present effectively even under adverse conditions
  • Strong project management, problem solving and troubleshooting skills with the ability to exercise mature judgment
  • Strong presentation and communication skills
  • Located and able to work in the U.S. from a home office and able to travel up to 50%

Key Responsibilities:

  • Data mining using state-of-the-art methods 
  • Extending client's data with third-party sources of information when needed 
  • Enhancing data collection procedures to include information that is relevant for building analytics and machine learning systems 
  • Processing, cleansing, and verifying the integrity of data used for analysis 
  • Doing ad-hoc analysis and presenting results in a clear manner 

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