Data Science Research Engineer

CCAMDisputanta, VA
2d

About The Position

The Commonwealth Center for Advanced Manufacturing (CCAM) is seeking a Data Science Research Engineer to join multidisciplinary teams comprising industry technical leaders, academic experts, and researchers. In this role, you will contribute to the development and implementation of data-driven solutions addressing real-world challenges in advanced manufacturing. This position offers a unique opportunity to collaborate with leading companies while delivering work that directly advances manufacturing technologies. CCAM is a non-profit applied research organization located in Disputanta, Virginia (just south of Richmond) and operates from a modern, state-of-the-art facility designed to foster innovation and impactful research. POSITION SUMMARY The Data Science Research Engineer advances CCAM’s manufacturing research by developing and applying data science, machine learning, and computer vision methods to complex, multi-modal manufacturing datasets. Working within multidisciplinary teams, this role designs experiments, analyzes large-scale sensor and process data, and generates actionable insights that improve manufacturing quality, efficiency, and reliability. One area where this role is expected to make an impact is additive manufacturing, which is a major area of emphasis for CCAM. Additional areas of interest include other methods of advanced manufacturing such as coating processes and subtractive manufacturing. In this role, the Data Science Research Engineer supports and leads the full research lifecycle, including problem scoping, technology evaluation, numerical method development, validation, and solution integration. The position requires close engagement with subject matter experts and process owners across industry, government, and academia, as well as the ability to communicate technical results to diverse audiences. Researchers in this role thrive in a fast-paced, collaborative environment, contribute to mentoring and knowledge sharing, and work across multiple concurrent projects to deliver impactful manufacturing innovations.

Requirements

  • Bachelor’s in Engineering, Data Science, Computer Science, Statistics, Mathematics, or related field.
  • Strong proficiency in analytical, visualization and modeling tools based in Python (e.g., NumPy, Pandas/Polars, Scikit-learn, OpenCV, TensorFlow or PyTorch, Streamlit, Matplotlib/Plotly).
  • Experience designing, running, and analyzing large dataset results from experiments intended to develop a better fundamental understanding of certain processes or models
  • Strong communication and technical writing skills.
  • This position requires access to technology or intellectual property that is subject to export control requirements. Candidates must be qualified for such access without an export control license.

Nice To Haves

  • Advanced degree (M.S. or Ph.D.) in Engineering or related STEM field with relevant experience.
  • 1+ year of work experience in data science, analytics, or applied ML.
  • Prior work in applied research or collaborative R&D environments.
  • Knowledge of sensing technology, image and signal processing, computer vision, computational modeling, and process monitoring.
  • Knowledge of advanced manufacturing technologies: additive manufacturing (SLM and DED), coating systems (HVOF, plasma thermal spray, cold spray), and subtractive manufacturing (chip forming processes, grinding and forming)
  • Familiarity with databases (SQL, MongoDB, Influx) and cloud environments (AWS, Azure).

Responsibilities

  • Function as a subject matter expert in data science specialties to develop and deploy algorithms and methods for detection, prediction, and modeling that result in actionable decisions driving a particular manufacturing process.
  • Collect, preprocess, and analyze data from advanced manufacturing systems. Analysis will encompass processing of image data, high frequency acoustic data, spatial data (e.g. high density point clouds) and time series data, among others.
  • Perform data processing, analysis, and visualization using statistical modeling, traditional machine learning (ML) and state-of-the-art deep learning (DL) approaches leveraging ML frameworks and Python libraries.
  • Customize and fine-tune ML and DL models to support anomaly detection, segmentation, classification, and regression across numeric, image-based, and time-series manufacturing data.
  • Develop pipelines for parsing custom data formats and managing structured/unstructured datasets.
  • Apply critical thinking to test hypotheses about manufacturing processes, part quality, performance, etc.
  • Identify and prioritize areas of uncertainty and risk governing data science models and predictions that affect overall application.
  • Engage with the data science community globally and locally to understand current innovations, emerging technologies, and relevant standards.
  • Collaborate closely with clients to understand their business challenges and develop technical solutions aligned with organizational objectives.
  • Break down complex technical problems and solutions into clear, concise insights and recommendations for stakeholders and non-technical executives.
  • Work with cross-functional teams to design experiments and data collection protocols.
  • Communicate findings to internal researchers and external collaborators.
  • Present technical results in clear, compelling formats to CCAM teams and member organizations.
  • Support hypothesis-driven research in manufacturing science.
  • Contribute to written communications such as reports and proposals related to advanced manufacturing analytics.

Benefits

  • Health, Dental, Vision insurance plan options; eligible on first of month following date of hire.
  • HRA – Health Reimbursement Account (employer funded, covers a portion of the medical deductible).
  • FSA – Flexible spending Account (employee funded, pre-tax).
  • 401k Retirement Plan – Employer contributes 3% of base salary monthly; additional discretionary match up to 7.5% determined annually starting 6 months after employment.
  • Life, Accidental Death & Dismemberment, Short Term Disability, and Long-Term Disability insurance (employer funded).
  • 3 weeks paid vacation.
  • 2 weeks paid maternity/paternity/adoption leave.
  • Tuition Reimbursement up to $5250.00 per year.
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