Reporting Developer Senior- Data Scientist Senior

Reporting Developer Senior – Data Scientist Senior in GAC Savannah

Unique

Skills:

• Minimum 5 years experience in Data Science
• Programming: Expert level Python for ML and data engineering; strong modular coding practices, packaging, unit testing (pytest).
• Databricks (Azure), Microsoft Fabric, or AWS Sage Maker: Hands‑on experience with Lakehouse / Warehouse patterns, Spark Data Frames, Delta Lake (ACID, OPTIMIZE/VACUUM), MLflow for experiment tracking, model registry, and jobs/workflows.
• ML Tooling: Scikit‑learn, XGBoost/Light
  
  GBM, stats models; feature engineering at scale; model selection, cross‑validation, hyperparameter tuning; robust performance diagnostics (ROC/AUC, PR, F1, lift, residual/error analysis).
• Data Ops & MLOps: MLflow, model packaging, batch/stream inference patterns on Databricks, job orchestration, CI/CD for notebooks/repos, environment reproducibility (conda/poetry), and model monitoring (drift, stability, recalibration triggers).

• Classical ML focus (non‑GenAI): Time series forecasting (ARIMA/SARIMA/ETS/Prophet, gradient boosting for forecast blending), supervised learning (classification, regression), unsupervised learning (clustering, anomaly detection), survival/reliability analysis, and design of experiments (DOE).
• Feature engineering: Lag/lead features, calendar/maintenance cycles, sensor aggregation windows, rolling stats, treatment of missingness/outliers, target leakage controls, and robust scaling for heteroscedastic industrial data. Synthetic data generation.
• Evaluation in production contexts: Backtesting strategies, cross‑site validation (multi‑plant / multi‑airframe), cost‑sensitive metrics (false alarm vs miss costs), and explainability suitable for engineering review boards. Optimization of Type 1 vs. Type 2 errors.

• Industrial analytics:
  
  Experience with
  predictive maintenance
  , condition‑based monitoring
  , yield/throughput improvement,
  quality/defect analytics
  , SPC, first‑pass yield, and takt‑time bottleneck analysis in complex discrete manufacturing.
• Aerospace value chain: Practical familiarity with E2E flows: design supply chain, assembly, test/flight, field operations & MRO; interpreting sensor/telemetry (AHTMS), maintenance logs, and part lifecycle histories.
• ERP/MES/PLM context: Working knowledge of SAP/ERP data constructs (orders, routings, WIP, inventory), MES event logs, and engineering change impacts on data semantics.

• Stakeholder engagement: Translate business problems into solvable ML formulations; quantify expected value; define acceptance criteria; present results to engineering, reliability, and operations leaders.
• Cross‑functional teaming: Close collaboration with Data Engineering (ETL, CDC, quality, security) and Citizen Data Scientists for enablement and review cycles.
• Documentation & training: Produce clear technical docs, model cards, and operational runbooks; coach junior DS and citizen developers.

Bachelor's Degree in Information Technology, Computer Science, Engineering or relevant curriculum required or equivalent combination of education and experience sufficient to successfully perform the essential functions of the job. 9 years relevant business/technical experience to include five (5) years specific reporting, data analytics, or related technical development/deployment experience. Master's Degree may be used to offset one (1) year of experience;
PhD may offset two (2) years of experience.

This is a data and analytics development role within the Gulfstream Business Technology organization for the Enterprise Reporting team. This role directly supports the suite of Gulfstream Enterprise Reporting applications. Responsible for developing requirements, solution development, testing, deployment, and support of enterprise reporting solutions.

Principle Duties and Responsibilities:

Essential Functions: