Machine Learning Engineer/Data Scientist

Overview

Remote
Depends on Experience
Contract - W2
Contract - 2 Year(s)

Skills

Machine Learning
Amazon SageMaker AI
ML pipelines
ML Operations
MLFlow
GitHub
Docker

Job Details

Position: Machine Learning Engineer/Data Scientist
Location: Fully Remote (USA)

Contract: 6-9M Contract to hire
Openings: 1-2 openings (Senior)

Job Description:
Machine Learning Engineer/Data Scientist:

Deliver insights to help our clients turn data into action as a Data Scientist Advisor. Your work will provide transformative solutions to our clients big-data obstacles and help advance the mission. Here, you can make a meaningful impact on our clients mission and on your career.

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers.

HOW A DATA SCIENTIST ADVISOR WILL MAKE AN IMPACT

  • Develop data science / Machine Learning (ML) / Artificial Intelligence (AI) solutions to complex business challenges.
  • Utilize advanced data science tools and skills to interpret, connect, predict, and make discoveries in data.
  • Use predictive modeling to increase and optimize customer experiences, efficiencies, process improvements, and other business outcomes.
  • Manage and analyze large and/or complex datasets.
  • Provide support in capturing and defining any requirements for the deliverables/ solutions for the projects under this contract.
  • Provide expertise and implementation support for projects in data science, predictive analytics, machine learning, and artificial intelligence.
  • May coach and review the work of less-experienced professionals.

WHAT YOU LL NEED TO SUCCEED:

Education: Masters of Science in Data Science, or similar degree

Required Experience: 8+ years of related experience

Required Technical Skills: **Specific skill sets required**

  • Proven experience developing machine learning models and engineering features using Python, Spark, and other packages in Amazon SageMaker AI
  • Able to create complex queries in SQL for testing and data analysis
  • Experience developing ML pipelines and with ML Operations
  • Experience with Model Tuning and Governance
  • Experience with the following tools: MLFlow, GitHub, Docker

Required Skills

  • Data Science, Data Analysis, Docker (Software), Feature Engineering, Interpersonal Communication, Machine Learning, Machine Learning Operations, MLFlow, Model Governance, Model Tuning, Predictive Modeling, Python (Programming Language), Strong writer and communicator

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

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