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# Reliability Engineer- Data Analytics

- **Company:** A.M. COMMUNICATIONS SOLUTIONS INC
- **Location:** Harrisburg, PA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Analysis of Variance (ANOVA), Data Centers, Data Visualization, R (Programming Language), Statistical Hypothesis Testing, Python (Programming Language), MATLAB, Machine Learning, Minitab, Statistical Process Control (SPC), SQL Databases, Network Switches, JMP (Statistical Software), Data Analytics, Data Pipelines
- **Published:** October 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=c2f04f662d77d041

## About the Role

* Bachelor's degree in engineering, reliability, statistics, data science, or a related quantitative field; advanced degree preferred.
 * 5+ years of experience in reliability, validation, quality, data analytics, or failure analysis; cable, connector, or high-speed interconnect experience preferred.
 * Proficiency in reliability statistics, life-data and accelerated-test modeling, sampling methods, confidence bounds, and regression.
 * Experience with Six Sigma methods and tools; Green Belt or equivalent practical experience preferred.
 * Proficiency with JMP, Minitab, Python, R, SQL, MATLAB, or comparable analytics and visualization tools.
 * Hands-on experience with electrical, mechanical, and environmental testing and with diagnosing mixed failure modes.
 * Strong analytical, technical leadership, and communication skills.
 * Ability to travel up to 30%, * Experience with HALT, HASS, ALT, ORT, and ESS methodologies.
 * Experience with AI data centers, hyperscale infrastructure, or high-speed copper and hybrid cable technologies.
 * Experience with predictive analytics, machine learning, anomaly detection, or reliability data pipelines.
 * Familiarity with Manufacturing Execution Systems (MES) and manufacturing data integration, traceability, and analytics.
 * Six Sigma Black Belt, Certified Reliability Engineer, or comparable certification.
 * Familiarity with IPC, IEC, Telcordia, or MIL-STD standards and FIT, MTBF, warranty, or return-rate analytics.

## Description

* Develop data-driven reliability and robustness strategies across the product life cycle.
 * Analyze reliability, manufacturing, FRACAS, RMA, and field data to identify trends, failure patterns, and systemic risks.
 * Apply regression, ANOVA, hypothesis testing, distribution analysis, and multivariate methods to support risk-based decisions.
 * Design and analyze experiments to identify critical factors and optimize product and process performance.
 * Lead Six Sigma and structured problem-solving efforts using DMAIC, DOE, MSA, SPC, 8D, and root-cause analysis.
 * Build reliability and life models using Weibull, Arrhenius, and physics-of-failure methods; correlate accelerated test results with field performance.
 * Automate analyses and dashboards that communicate reliability metrics, variation, leading indicators, and emerging risks.
 * Lead failure analysis and present clear technical conclusions and recommendations to cross-functional, executive, and customer stakeholders.