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YO IT 컨설팅

Data Scientist

YO IT Consulting

Remote · 정규직

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경험
어느
샐러리
채용 공고
1
게시됨
3시간전
작업 모드
재택근무
재개하다
신청 시 필수 사항

직무 설명

Overview

This contractor position for a Data Scientist is fully remote and involves leveraging your expertise to assist in training next-generation AI models. Although previous AI experience is not mandatory, your knowledge in your specialty will be pivotal in guiding how these models learn and perform using real-world data.

Core Responsibilities

  • Gather, cleanse, and preprocess various types of data to maintain integrity and prepare it for detailed analysis.
  • Create, verify, and implement statistical models that reveal meaningful insights from multifaceted data sets.
  • Perform exploratory analysis to detect trends, patterns, and business growth opportunities.
  • Deliver results and suggestions through engaging visualizations and reports suited for both technical and non-technical audiences.
  • Work collaboratively with team members to oversee data projects from conception through to completion.
  • Enhance data processes by refining analytics techniques and automating workflows continuously.
  • Communicate clearly and effectively in written and verbal formats, emphasizing precision in conveying data insights.

Required Skills and Qualifications

  • Strong foundation in statistics, mathematics, and data analysis methods.
  • Demonstrated experience in collecting and preparing large and complex datasets.
  • Proficiency in programming languages like Python, R, or equivalents for data handling and modeling tasks.
  • Competence in constructing and validating predictive data models.
  • Advanced skills in data visualization using tools such as Tableau, Power BI, or relevant visualization libraries.
  • High attention to detail ensuring data quality throughout the analytical process.
  • Exceptional abilities in both verbal and written communication aimed at clarity and accuracy.

Preferred Qualifications

  • Experience collaborating within remote, multifunctional, or client-oriented teams.
  • Background in implementing and maintaining machine learning models in live environments.

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