Data Scientist

Remote • Posted 12 hours ago • Updated 7 hours ago
Contract Independent
Contract W2
Remote
Fitment

Dice Job Match Score™

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Job Details

Skills

  • Python
  • Datasets
  • SQL
  • Statistical Analysis
  • Machine Learning
  • Optimization
  • Predictive Modeling
  • Clustering
  • Anomaly Detection
  • Process Control
  • Statistical Process Control
  • Calibration
  • SSBI
  • Supervised Learning
  • Autoencoders
  • Boosting
  • Time-Series
  • Encoding

Summary

Job Title: Data Scientist
Location: Remote
Clearance: Active Top Secret
Job Type: Contract W2


Top Skills
Strong background building and deploying machine learning models.
Experience with:
o Predictive modeling
o Classification
o Clustering
o Statistical analysis
o Feature engineering
o 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
o U.S. citizenship and active T5/SSBI federally adjudicated clearance required.
o Hands-on Databricks.
o Feature engineering on tabular and time-series data - encoding, aggregation, leakage prevention, and selection grounded in domain reasoning rather than automated search alone.
o Supervised learning on tabular data: gradient boosting (XGBoost/LightGBM), regularized regression, and the judgment to know when the simpler model is the right answer.
o Model calibration and evaluation under class imbalance - you can explain why AUC alone is insufficient for a risk score.
o Anomaly detection: isolation forests, autoencoders, statistical process control, or comparable - with a clear account of how you validated detections without labels.
o Optimization: LP/MIP or heuristic methods (OR-Tools, Pyomo, SciPy, or equivalent) applied to a real allocation or prioritization problem.
o Explainability (SHAP or comparable) in a decision-support context.
o 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.
o Strong Python, SQL, and Spark.
o Government or defense contracting experience.
Thanks and Regards,
Murali Sharma

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
  • Dice Id: 91142412
  • Position Id: 2026-2293
  • Posted 12 hours ago
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