Digital Biomarker Biomedical Engineer

Focus: Provide signal processing expertise to support algorithm validation, investigate data discrepancies, and help establish confidence in system equivalency during platform or environment transitions.

Responsibilities:

-Provide technical guidance on signal processing to migration, engineering, and clinical teams, ensuring a shared understanding of algorithm behaviour and expected output characteristics.

-Analyse datasets to identify deviations, edge cases, and anomalies, including those introduced by changes in compute environments or data pipelines. Apply appropriate statistical methods to assess whether discrepancies are meaningful.

-Deconstruct the logic of existing signal processing algorithms and produce clear, well-structured documentation to support computer system validation (CSV) efforts and enable knowledge transfer across teams.

-Contribute to the design of validation frameworks and test cases, including the definition of tolerance thresholds and acceptance criteria for comparing algorithm outputs across environments.

-Develop and execute CSV-based comparison workflows to verify the consistency of algorithmic output. Identify, classify, and quantify discrepancies, distinguishing between acceptable numerical precision variation and genuine regressions.

-Collaborate with data migration specialists and engineers to resolve data-integrity issues. Ensure that all deviations are properly quantified, documented, and traceable for review and sign-off.

Qualifications:

-PhD in Electrical Engineering, Applied Mathematics, Physics, Data Science, or a related quantitative field.

-Solid understanding of digital signal processing and time-series analysis.

-Proficiency in Python, including familiarity with libraries like SciPy, NumPy, or pandas.

-Experience with algorithm or software validation, including defining acceptance criteria and tolerance thresholds. Formal V&V experience is preferred, but equivalent structured testing experience is acceptable.

-Experience developing data comparison or reconciliation workflows using large tabular or CSV datasets.

-Demonstrated ability to produce clear technical documentation for diverse audiences.

-Able to communicate complex technical concepts to stakeholders outside your speciality.

Preferred:

-Familiarity with database migrations or platform equivalency testing.

-Exposure to version-controlled analysis workflows or reproducible research practices.

-Experience with high-frequency sensor data.