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Salary: USD 145,000 - 180,000 / annual
Archer Technologies is a Silicon Valley-based aerospace company building advanced air mobility platforms, including electric aircraft, unmanned aircraft systems (UAS), and AI-powered aviation software. The AI Products Org is a ~100-person software division within the larger aerospace engineering company, building consumer software for the general aviation industry.
As a Senior Data Scientist, you will bridge raw, messy aviation data and the intelligence powering Archer's AI platform. You'll work with high-frequency aircraft telemetry and noisy air traffic control audio to determine what is actually happening in the sky.
Key Responsibilities:
- Derive new signals from high-throughput, real-time data streams, inferring complex physical and operational states not directly observable in raw telemetry
- Build, evaluate, and iterate on models across diverse modalities: dense time-series, spatial data, and highly noisy, unstructured sequential data
- Design evaluation frameworks for problems with little or no labeled ground truth, using weak supervision and programmatic labeling; defend these definitions to engineers and domain experts
- Partner with backend and platform engineers to move models from offline analysis into production streaming pipelines, and own their behavior once live
- Work directly with aviation subject-matter experts to translate operational knowledge into features, labels, and evaluation criteria
- Leverage AI assistants to increase velocity while maintaining full ownership of every model, feature, and analysis shipped
The role offers the resources and momentum of an established org while working on early-stage products that are real, ship regularly, and have active users. Expect substantial team growth over the next year.
Requirements:
- BS/MS/PhD in Computer Science, Statistics, Applied Mathematics, Operations Research, Aerospace Engineering, or related quantitative field
- 2+ years of applied data science or machine learning experience, including models deployed to production
- Strong Python and SQL proficiency over large analytical datasets
- Depth in time-series and sequence modeling
- Experience working with sparse, incomplete, or unlabeled data—weak supervision, programmatic labeling, and building evaluation sets without ground truth
- Experience designing data validation and drift detection for continuously arriving data
- Strong communication skills and collaborative mindset; ability to explain methodology and limitations to non-specialist audiences
Bonus Qualifications:
- Prior experience or deep interest in aerospace, aviation, or high-throughput tracking systems (flight telemetry, ATC phraseology, airspace procedures)
- Familiarity with geographic/spatial data processing (projections, spatial indexing, great-circle geometry)
- Awareness of distributed messaging and stream-processing systems (Apache Pulsar, Kafka, Apache Flink) and columnar or lakehouse analytical storage
