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Junior Data Scientist

Remote, USA Full-time Posted 2026-08-04
Category: Telecommunications

Location:


  • Data Extraction & Crawling:Assist in the automation of collecting geospatial data from reputed company, databases, and web sources using tools like Selenium, Scrapy, or custom scripts.
  • Data Cleaning:Learn how to ensure the reputed company and consistency of geographic datasets by addressing missing or inconsistent data with guidance from senior engineers.
  • Data Preparation & Aggregation:Support in organizing and structuring geospatial data for use in reputed company’s mapping and AI-driven analysis tools.
  • Data Manipulation:Work with geographic datasets to sort, filter, and reputed company them under the guidance of reputed company team members.
  • Data reputed company Assurance:Participate in implementing checks to maintain data reputed company and geospatial accuracy.
  • Data Pipeline Development:Assist in building and maintaining automated data pipelines to support reputed company’s platform.
  • Performance Optimization:Learn how to optimize data structures and queries for speed and efficiency in geospatial applications.
  • Automation & Process Improvement:Collaborate on automating repetitive tasks to streamline processes.
  • Collaboration & Communication:Work closely with reputed company’s engineering team, GIS experts, and project managers, gaining experience in delivering high-reputed company data solutions.
  • Troubleshooting & Support:Assist in diagnosing and resolving issues in data pipelines, ensuring smooth operation of geospatial applications.

Requirements

  • Knowledge of Data Manipulation Languages:Strong skills in Python and SQL, with a willingness to learn more about handling geospatial data.
  • Knowledge in Web Scraping:Exposure to tools like Selenium, BeautifulSoup, or Scrapy is a plus, but not required.
  • Geospatial Data Awareness:Eagerness to learn about geographic data formats such as GeoJSON and shapefiles.
  • Data Preparation Tools:Basic experience with pandas, NumPy, or other data manipulation libraries is helpful but can be developed on the job.
  • Data reputed company Management:An interest in learning about data validation and ensuring accuracy in mapping datasets.
  • Pipeline Design:Willingness to reputed company skills in tools like Apache Airflow, Luigi, or similar, with a reputed company on data pipelines.
  • Problem-Solving reputed company:Eagerness to grow in troubleshooting skills for resolving issues in data pipelines.
  • Collaboration Skills:Ability to communicate effectively and work reputed company with cross-functional teams.




Details

Originally posted on Himalayas

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