Data Scientist

Job Title: Data Scientist

Location: Remote

Job Type: Contract W2

Clearance: with Active Top Secret

Top Skills

Strong background building and deploying machine learning models.

Experience with:

Predictive modeling

Classification

Clustering

Statistical analysis

Feature engineering

Model evaluation

Experience preparing, cleaning, and curating large datasets.

Hands-on experience with Databricks preferred.

Experience creating synthetic datasets is a plus.

Comfortable taking models from concept through production.

Looking for candidates who enjoy solving business problems with data and can work independently.

Required Qualifications

U.

S. citizenship and active T5/SSBI federally adjudicated clearance required.

Hands-on Databricks.

Feature engineering on tabular and time-series data - encoding, aggregation, leakage prevention, and selection grounded in domain reasoning rather than automated search alone.

Supervised learning on tabular data: gradient boosting (XGBoost/LightGBM), regularized regression, and the judgment to know when the simpler model is the right answer.

Model calibration and evaluation under class imbalance - you can explain why AUC alone is insufficient for a risk score.

Anomaly detection: isolation forests, autoencoders, statistical process control, or comparable - with a clear account of how you validated detections without labels.

Optimization: LP/MIP or heuristic methods (OR-Tools, Pyomo, SciPy, or equivalent) applied to a real allocation or prioritization problem.

Explainability (SHAP or comparable) in a decision-support context.

Privacy-preserving synthetic data generation from CUI, PII, or comparably restricted source data - relational tabular data with distributional fidelity, cross-column correlations, referential integrity, and preservation of the rare-event structure that anomaly detection and risk scoring depend on. Includes an understanding of re-identification risk.

Strong Python, SQL, and Spark.

Government or defense contracting experience.