Entry-Level Data Scientist

Military Spouse Corporate Career Network•Washington, DC

1d•Hybrid

About The Position

Amida Technology Solutions is seeking a highly motivated Entry-Level Data Scientist to apply academic training to real-world projects and develop skills alongside experienced mentors. The role supports projects involving graph algorithms and techniques for advanced data management designs, including dimension-rich and time-series-based decision systems. The position is 40 hours per week. The initial three months are a temporary, hourly engagement, with the possibility of conversion to a full-time position based on performance and business needs. Candidates must be able to work three days per week at the company's Washington, DC headquarters. Candidates must be U.S. citizens or Green Card holders and have at least one of the listed additional skillsets. Amida is a DC-based technology company focused on data interoperability, integrity, governance, and security. It develops solutions to collect, reconcile, transform, and standardize data for business intelligence, advanced analytics, decision support, and user transactions. Its work environment is described as entrepreneurial and high-growth, with an emphasis on fresh ideas, candid conversations, and teamwork.

Requirements

Bachelor's degree in computer science, mathematics, or engineering; a strong focus on graph theory, algorithms, and data structures is preferred.
Demonstrated passion for data science and eagerness to learn new techniques and technologies.
Working knowledge of Python.
Enjoy collaboration.
Superior communication skills.
Excellent organizational skills.
Attention to detail.
Self-motivated.
Must be a U.S. citizen or Green Card holder.
Must have at least one of the following skillsets: familiarity with graph and machine-learning libraries and frameworks (e.g., PyTorch Geometric, DGL, GDS); experience with NumPy, Pandas, and Matplotlib; Azure Databricks; graph algorithms or techniques; software testing concepts or methodologies; software development; or Cypher or Gremlin query language.

Nice To Haves

A strong academic focus on graph theory, algorithms, and data structures.
A sense of humor is an asset.

Responsibilities

Design, implement, and optimize graph algorithms and data structures for decision-support and classification applications.
Help create and implement algorithms for encoding and embedding, clustering, outlier detection, community detection, and dimensionality reduction.
Build distributed training pipelines capable of handling large graphs of 100 million or more graph elements.
Design and write queries and stored procedures for data loading, migration from existing databases, and data retrieval.
Contribute to white papers and technical documentation.