Lead Data Scientist

Streamline media groupLas Vegas, NV
15d

About The Position

Job Responsibilities: Manage data scientist and data specialist team. Identify the efficient source for quality data collection, Lead data collection and data mining processes. Ensure and guarantee data integrity. Analyze data and interpret data problems. Plan project, prioritize and streamline all planned data projects. Develop a proper analytic system according to the requirements. Analyze and test the performance of the products. Build reports on the visualization and performance of the products. keep implementing new techniques and models. Line up the data projects according to the goals of the company. Job Skills: Bachelor’s degree in Data Science, Computer Science, or other related fields. Proven experience in Data Science and other related fields. Good understanding o techniques of data management and visualization. Expertise in statistical data analysis and predictive data modeling. Good technical and coding knowledge of Python, R language, MATLAB, SQL, and other databases. Outstanding communication skills. Inspiring leadership qualities and organizational skills.

Requirements

  • Bachelor’s degree in Data Science, Computer Science, or other related fields.
  • Proven experience in Data Science and other related fields.
  • Good understanding o techniques of data management and visualization.
  • Expertise in statistical data analysis and predictive data modeling.
  • Good technical and coding knowledge of Python, R language, MATLAB, SQL, and other databases.
  • Outstanding communication skills.
  • Inspiring leadership qualities and organizational skills.

Responsibilities

  • Manage data scientist and data specialist team.
  • Identify the efficient source for quality data collection
  • Lead data collection and data mining processes.
  • Ensure and guarantee data integrity.
  • Analyze data and interpret data problems.
  • Plan project, prioritize and streamline all planned data projects.
  • Develop a proper analytic system according to the requirements.
  • Analyze and test the performance of the products.
  • Build reports on the visualization and performance of the products.
  • keep implementing new techniques and models.
  • Line up the data projects according to the goals of the company.
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