The Senior Data Analyst will lead the analytical direction behind retrospective data analysis, partnering closely with Data Engineering to transform raw telemetry into refined data narratives for stakeholders and end users. This onsite role is based in Ivyland, PA.
Responsibilities
- Lead the intersection of wearable sensor hardware and advanced analytics, producing well-documented analysis tools and notebooks on top of the data lake maintained by Data Engineering, and training others to use them.
- Work directly with raw biosignals to interpret complex physiological data and translate it into usable insights.
- Define requirements for, and curate content of, a physiological recordings metadata database in partnership with Data Engineering, ensuring inventory and provenance remain accurate across all hardware generations.
- Manage the inventory and provenance of both legacy and new datasets to support downstream data products.
- Build comprehensive data products end-to-end, owning the path from concept to delivery for audiences ranging from engineers to the C-suite and end users, including high-fidelity pathology visualizations and rigorous statistical reporting.
- Ingest and curate multi-source, time- and location-tagged data, define ontologies and analytical requirements to extract meaningful signals, and collaborate with Data Engineering on the pipelines that support them.
- Create lighthouse data products that establish organization-wide standards for analysis and data presentation.
- With the Algorithm Development team, contribute to early-stage proof-of-concept methods that can evolve into internal and externally facing products.
- Serve as the primary investigator for data anomalies by investigating through the hardware-to-cloud stack, identifying likely root causes, and partnering with responsible engineering teams on resolution.
- Partner with engineers, product leads, and stakeholders to understand the “why” behind the data and translate business needs into essential internal tooling.
- Design and operate evaluation tools for the Ascent system, implementing robust statistical models and ML workflows for automated anomaly detection and trend analysis.
- Rapidly adapt to an evolving hardware/software ecosystem by updating pipelines and visualizations to maintain data visibility as capabilities change.
Requirements
- Strong experience with Python or MATLAB (or equivalent) for data transformation and post-processing.
- Experience working with regulated data, including coding and handling sensitive medical or industrial data (for example, HIPAA, PII/PHI).
- Experience with scientific data formats including HDF5, MATLAB, and Parquet.
- Demonstrated ability analyzing large, complex datasets at TB to PB scale.
- Experience curating heterogeneous legacy datasets and defining metadata requirements; data modeling experience is a plus.
- Strong software engineering practices, including Git, code review, CI, and rigorous test and validation.
- Proven track record of technical data analysis and presentation.
- Ability to work independently across teams and stakeholders.
- Demonstrated success in a results-oriented, fast-paced, dynamic environment.
- Master’s degree in computer science, computer engineering, or a related technical discipline, or 15+ years of experience in total preferred.
- 10+ years of experience in Software Development with at least 7+ years acting as a Data Analyst or Data Scientist.
Technologies
Python, MATLAB, JavaScript, TypeScript, Rust, R, C/C++, HDF5, Parquet, Git, CI, Adobe Illustrator, Adobe Premiere, After Effects, Blender, Maya, GIS, ECG, PPG, accelerometry, ML, Ascent system.
Education and Experience
- Master’s degree in computer science, computer engineering, or a related technical discipline, or 15+ years of experience in total preferred.
- 10+ years of experience in Software Development with at least 7+ years acting as a Data Analyst or Data Scientist.
Benefits
- Health Insurance
- Dental & Vision Insurance
- Paid Time Off
- 401(k)
- Stock option incentive plan
- FSA & dependent care
