Reporting Developer III - Data Scientist

General Minimum 3 years experience in Data Science Programming: Python for ML and data engineering; strong modular coding practices, packaging, unit testing (pytest). Databricks (Azure) or Microsoft Fabric or AWS Sagemaker: Hands‑on experience with Lakehouse / Warehouse patterns, Spark DataFrames, MLflow for experiment tracking, model registry, and jobs/workflows. ML Tooling: Scikit-learn, XGBoost/LightGBM, statsmodels; 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, job orchestration, CI/CD for notebooks/repos. 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, treatment of missingness/outliers, and robust scaling for heteroscedastic industrial data. Synthetic data generation. Evaluation in production contexts: Cost‑sensitive metrics (false‑alarm vs miss costs), explainability suitable for engineering review boards. Optimization of Type 1 vs. Type 2 errors. Manufacturing & Aerospace Domain (Preferred) 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. 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, operational runbooks; coach citizen developers. Education and Experience Requirements 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. 6 years relevant business/technical experience to include three (3) 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. Position Purpose : 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. Job Description Engages stakeholders and technology users in identifying, analyzing, and documenting business requirements. Ensures application processes are followed consistently and are in compliance with applicable policies, procedures, standards, etc. Performs normal administration tasks and system maintenance for reporting and data analytics applications and solutions. Documents, develops, tests, deploys, and supports reporting and data analytics development using a variety of technical tools in support of business requirements. Conducts briefings and participates in technical meetings concerning specific projects or other activities. Performs other duties as assigned. Experience with Agile development methodology and working on an agile team preferred. Demonstrated understanding of software development lifecycle methodologies (SDLC). Experience in conducting testing including design and execution of test cases. Demonstrated capability to understand data structures and create effective visualizations and reports that drive business insight and value. Excellent presentation design and delivery skills. Ability to lead/facilitate cross‑functional teams and meetings. Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans #J-18808-Ljbffr