Junior Data Scientist

Category: Telecommunications Location: Data Extraction & Crawling: Assist in the automation of collecting geospatial data from APIs, databases, and web sources using tools like Selenium, Scrapy, or custom scripts. Data Cleaning: Learn how to ensure the quality 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 xMap ’s mapping and AI-driven analysis tools. Data Manipulation: Work with geographic datasets to sort, filter, and transform them under the guidance of experienced team members. Data Quality Assurance: Participate in implementing checks to maintain data integrity and geospatial accuracy. Data Pipeline Development: Assist in building and maintaining automated data pipelines to support xMap ’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 xMap ’s engineering team, GIS experts, and project managers, gaining experience in delivering high-quality 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 Quality Management: An interest in learning about data validation and ensuring accuracy in mapping datasets. Pipeline Design: Willingness to develop skills in tools like Apache Airflow, Luigi, or similar, with a focus on data pipelines. Problem-Solving Mindset: Eagerness to grow in troubleshooting skills for resolving issues in data pipelines. Collaboration Skills: Ability to communicate effectively and work well with cross-functional teams. Details Originally posted on Himalayas