Reporting Developer Senior- Data Scientist Senior

Gulfstream • Savannah, GA

1d

About The Position

Reporting Developer Senior- Data Scientist Senior in GAC Savannah Unique Skills: General: 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 Sagemaker: Hands‑on experience with Lakehouse / Warehouse patterns, Spark DataFrames, Delta Lake (ACID, OPTIMIZE/VACUUM), 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, batch/stream inference patterns on Databricks, job orchestration, CI/CD for notebooks/repos, environment reproducibility (conda/poetry), and model monitoring (drift, stability, recalibration triggers). Machine Learning Expertise 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. Manufacturing & Aerospace Domain (Strongly 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. Collaboration, Communication & Leadership 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. 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. 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. 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.

Requirements

• Minimum 5 years experience in Data Science
• Expert‑level Python for ML and data engineering; strong modular coding practices, packaging, unit testing (pytest).
• Hands‑on experience with Lakehouse / Warehouse patterns, Spark DataFrames, Delta Lake (ACID, OPTIMIZE/VACUUM), MLflow for experiment tracking, model registry, and jobs/workflows.
• 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).
• 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).
• 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).
• 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.
• 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.
• 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.
• Demonstrated understanding of software development lifecycle methodologies (SDLC).
• Experience in conducting testing including design and execution of test cases.
• Demonstrated capability to understand high volume / high complexity data structures to deliver analytics solutions that drive business insight and value.
• Excellent presentation design and delivery skills.
• Ability to lead/facilitate cross-functional teams and meetings.
• This job requires one to be able to read, write, speak, and understand the English language.

Nice To Haves

• Manufacturing & Aerospace Domain (Strongly 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.
• Experience with Agile development methodology and working on an agile team preferred.
• Multiple agile based project deliveries and certified scrum master preferred.

Responsibilities

• Engages stakeholders and technology users in identifying, analyzing, and documenting business requirements.
• Creates plans according to schedules and assignments, and acts independently to carry them out.
• Assures that solution designs meet requirements for scalability, performance and quality in accordance with negotiated service level agreements.
• Drives decisions related to architecture and design.
• Delegates tasks and/or responsibilities to team members for action according to their level of experience and assigned accountability.
• Ensures applications processes are followed consistently and are in compliance with applicable policies, procedures, standards, etc.
• Performs work related to configuring, deploying, maintaining, and upgrading reporting and data analytics applications and processes.
• Responsible for tasks related to the development and deployment of systems, methodologies, standards and processes that result in the ability to create and manage the technical solutions.
• Supports management in recruiting, hiring, and career development.
• Assists with the development of work breakdown structures, project plans, and skills required. to develop and implement applications.
• 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.
• Serves as technical expert in one or more applications within a portfolio.
• Perform other duties as assigned.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level