Data Analyst
The Data Analyst role at Confidential Client focuses on developing and implementing predictive maintenance algorithms and machine learning models to monitor the health of industrial equipment such as engines and pumps. The position involves analyzing high-frequency sensor data using signal processing and data science techniques, collaborating with engineering teams, and delivering actionable insights through visualizations and reports to prevent equipment failures.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Engineering.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
Confidential Client is hiring an entry-level Condition Monitoring Analytics Developer (Data Analyst) in Virginia Beach, VA. You will build, test, and deploy data-driven solutions to support predictive maintenance and equipment health monitoring across industrial assets (engines, pumps, rotating machinery).
- Develop, test, and validate predictive maintenance algorithms and machine learning models for industrial equipment, including engines and pumps
- Design and implement anomaly detection techniques to identify abnormal equipment behavior and potential mechanical failures
- Collect, clean, preprocess, and analyze high-frequency time-series data from IoT sensors, SCADA systems, and equipment telemetry
- Perform feature engineering and extract signal features from vibration, temperature, pressure, and other sensor streams
- Apply signal-processing techniques such as Fast Fourier Transform (FFT), spectral analysis, digital filtering, and time-domain analysis
- Analyze mechanical failure patterns (bearing wear, cavitation, misalignment, etc.) and translate findings into actionable insights
- Develop Python-based scripts and analytical models using Pandas, NumPy, SciPy, and Scikit-learn
- Create dashboards, reports, and visualizations to communicate equipment health trends and predictive-maintenance recommendations
- Collaborate with Reliability, Mechanical, Data Science, and Software teams to validate models and support deployment to cloud or edge platforms
- Troubleshoot data-quality issues, tune model performance, and document model development and test results
Qualifications
- Bachelor’s degree in Mechanical Engineering, Aerospace Engineering, Mechatronics, Computer Science, Data Science, or a related quantitative field
- 2+ years working with Python (preferred) or R for data analysis and modeling
- Hands-on experience with Pandas, NumPy, SciPy, and Scikit-learn
- Knowledge of time-series analysis and signal-processing concepts (FFT, digital filtering)
- Familiarity with mechanical engineering fundamentals: engines, pumps, thermodynamics, fluid mechanics, and common failure modes
- Experience with data visualization tools (Power BI, Tableau, Plotly, Matplotlib)
- Strong analytical, troubleshooting, and problem-solving skills
- Clear written and verbal communication; ability to translate technical findings into actionable recommendations
Preferred Qualifications
- Academic projects, internships, or work experience in predictive maintenance, condition monitoring, or equipment health analytics
- Experience analyzing vibration, temperature, pressure, or other industrial sensor data
- Familiarity with rotating machinery, internal combustion engines, centrifugal pumps, or similar equipment
- Exposure to IoT platforms, SCADA systems, fleet telemetry, or edge-computing deployments
- Experience implementing machine learning algorithms for anomaly detection, classification, regression, or failure prediction
- Knowledge of reliability engineering, failure analysis, or condition-based maintenance
Location & Compensation
- Location: Virginia Beach, VA (on-site or as required by the Confidential Client)
- Employment type: Full-time
- Estimated pay: $87,638 per year (estimated)
Why Join
- Work on real-world predictive-maintenance and condition-monitoring challenges that directly impact asset reliability
- Collaborate with cross-functional engineering and data teams
- Opportunity to grow technical skills in signal processing, time-series analytics, and machine learning
- Exposure to both cloud and edge deployment workflows for industrial telemetry
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
Negotiate a higher salary! Check the salary ranges for this job type in your area.
View My Salary Range