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YO IT 컨설팅

Data Scientist - Remote

YO IT Consulting

Remote · 계약

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경험
어느
샐러리
채용 공고
1
게시됨
9시간전
작업 모드
재택근무
재개하다
신청 시 필수 사항

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Job Overview

We are offering a contractor position for a Data Scientist working remotely. The successful candidate will play a crucial role in supporting the development and training of advanced AI systems by providing high-quality, real-world data inputs. Prior AI experience is not mandatory; deep domain expertise is highly valued.

Key Responsibilities

  • Gather, clean, and preprocess varied datasets to guarantee their quality and suitability for analysis.
  • Create, test, and deploy statistical models that uncover meaningful insights from complex data.
  • Perform exploratory data analysis to discover trends and patterns that can drive business enhancement.
  • Deliver clear and impactful visualizations and reports customized for audiences with varying technical backgrounds.
  • Work collaboratively with team members to plan and complete comprehensive data projects from start to finish.
  • Refine analytical methods and automate processes to optimize data handling workflows.
  • Communicate findings and suggestions effectively, both in writing and orally, ensuring understanding and influence.

Required Skills and Qualifications

  • Strong foundation in statistics, mathematics, and data analytical techniques.
  • Demonstrated experience managing and cleaning complex, sizable datasets.
  • Proficiency in programming languages such as Python or R for data manipulation and model development.
  • Advanced competence in data modeling, including building and validating predictive algorithms.
  • Expertise in data visualization tools like Tableau, Power BI, or similar libraries.
  • Exceptional attention to detail and dedication to ensuring data quality during all phases.
  • Outstanding communication skills with a focus on clarity and accuracy in both written and spoken formats.

Preferred Qualifications

  • Experience working remotely in interdisciplinary or client-focused teams.
  • Familiarity with deploying machine learning models in production environments.

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