Associate Tech Specialist

Keylent, Inc.

$80K — $110K *
Plano, TX 75025In-Person
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5-7 years of experience manipulating data sets
  • MS or PhD in Statistics, Mathematics, or Computer Science
  • Knowledge of machine learning techniques including clustering, decision trees, and neural networks
  • Familiarity with advanced statistical techniques and their applications
  • Proficiency in data analysis tools using languages like R and Python
  • Experience with client-specific toolkits for model creation and visualization
  • Strong communication skills for cross-team collaboration

Responsibilities

  • Manipulate large data sets to extract valuable insights
  • Build and refine statistical and machine learning models
  • Conduct feature engineering to enhance model performance
  • Apply advanced statistical techniques to solve complex problems
  • Create visualizations to communicate model results and patterns
  • Collaborate with cross-functional teams to implement solutions
  • Continuously learn and adapt to emerging tools and technologies

Benefits

  • Flexible working arrangements
  • Opportunity for professional growth and advancement
  • Access to cutting-edge tools and technologies
  • Collaborative and inclusive work environment
  • Support for ongoing education and training opportunities
Full Job Description
Visa status: U.S. Citizens and those authorized to work in the U.S. are encouraged to apply.
Tax Terms: W2, 1099
Corp-Corp or 3rd Parties: Yes

We are looking for someone with 5-7 years of experience manipulating data sets, building statistical/machine learning models, has a MS or PhD in Statistics, Mathematics, or Computer Science, and has the following background/skills:
• Knowledge of a variety of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and experience in feature engineering and choosing proper Client algorism
• Knowledge of advanced statistical techniques and concepts (regression, properties of distributions, statistical tests and proper usage, etc.) and experience with for their applications
• Experience in Data DAD (Client/Access /Distill) using statistical computer languages (R, Python, etc.) to manipulate data and draw insights from large data sets
• Experience creating machine learning models using Client toolkits (RCloud, H2O, etc.) and visualize them for determining patterns
• Excellent written and verbal communication skills for working across teams
• drive to learn and master new technologies and techniques

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