Junior Data Scientist

This is a remote position.

• 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.