Space Surveillance Data Science Engineer

Neara; Denver, Northern (CO, KY); Hybrid; USD 120,000 - 170,000; Full time

Benefits offered by this job

Competitive salary

Benefits package

Equity

Job summary

Digantara U.S. is seeking an experienced Data Science Engineer to develop ML components and integration infrastructure supporting SDA analytics pipelines.

You will build trajectory-classification and anomaly-detection models that operate on orbit-determination output, and maintain benchmarking frameworks. The role collaborates with astrodynamics and embedded-systems teams to ensure models reflect genuine dynamical structure and fit onboard resource limits, with emphasis on calibrated confidence

Qualifications

• 4+ years of applied ML experience or equivalent.
• Strong Python and scientific stack proficiency.
• Experience with time-series or state-estimation data.
• Ability to obtain and hold a U.S. security clearance.

Responsibilities

• Develop ML models for trajectory classification and anomaly detection.
• Integrate end-to-end analytical pipelines spanning observation processing, orbit estimation, propagation, and classification.
• Build benchmarking and evaluation frameworks for estimator convergence and confusion matrices.
• Design experiments to distinguish genuine generalization from dataset artifacts.
• Produce calibrated confidence metrics for downstream operator use.
• Collaborate with embedded-systems staff to meet deployment constraints.

Skills

Python

NumPy

SciPy

pandas

PyTorch

Time-series ML

Model evaluation

Software engineering

Technical writing

US security clearance

Education

BS in Computer Science or related field

MS in related field

Tools

Git

Docker

ONNX

Job description

Digantara U.S. is seeking an experienced Data Science Engineer to develop ML components and integration infrastructure supporting SDA analytics pipelines.

You will build trajectory-classification and anomaly-detection models that operate on orbit-determination output, and maintain benchmarking frameworks. The role collaborates with astrodynamics and embedded-systems teams to ensure models reflect genuine dynamical structure and fit onboard resource limits, with emphasis on calibrated confidence