Maxar is seeking a Mid-Level Data Scientist to automate data workflows, clean and prepare large-scale datasets, and ensure reliable, well-structured data for advanced analytics and modeling to support a hard and deeply buried target mission set, providing critical analytic insights to government stakeholders.
Requirements
- Proficiency in Python and SQL; familiarity with R is a plus.
- Experience with data wrangling libraries (e.g., pandas, PySpark) and working with APIs or batch processing tools.
- Familiarity with ETL pipelines and orchestration tools (e.g., Apache Airflow, Clairvoyant, or similar).
- Comfortable working with large datasets in distributed environments (e.g., Spark).
- Foundational understanding of containers (e.g., Docker) and how they are used in deploying data workflows.
- Exposure to cloud platforms such as AWS, Azure, or GCP, especially in data-related services.
- Experience using Clairvoyant or similar orchestration platforms to manage and monitor data pipelines.
Responsibilities
- Automate ETL workflows and streamline repetitive data preparation tasks using Python, SQL, and scripting tools.
- Operate in big data ecosystems using tools such as Spark, Hadoop, or their cloud-native equivalents (e.g., AWS Glue, Azure Synapse, Databricks).
- Assist in the development and deployment of data pipelines in collaboration with data engineering and DevOps teams.
- Implement basic statistical analyses, visualizations, and reporting to support exploratory data analysis and hypothesis validation.
- Maintain detailed documentation of data preparation methods, scripts, and pipeline configurations.
- Support integration of data into downstream modeling and LLM/NLP workflows.
- Contribute to operationalizing data products, APIs, and internal data access tools.
Other
- Current/active TS/SCI security clearance and be willing and able to obtain CI polygraph.
- 5 years of professional experience in data science, analytics, or data engineering roles.
- Bachelor’s degree in data science, computer science, engineering, statistics, GIS, or related discipline. Degree may be substituted with an additional 2 yrs of experience.
- Strong attention to detail and documentation practices.
- This position is full time onsite in Reston, VA.
