Data Analyst Intern

AI Vision Processors For Edge Applications

Our solutions make cameras smarter by extracting valuable data from high-resolution video streams.

Job Description

Help our team develop and evaluate astrobiology‑focused AI models that run on Ambarella SoCs—without needing to write production code. You’ll focus on data curation, annotation, experiment setup, hardware‑in‑the‑loop testing, and scientific documentation. Think of this as being the “research operations” engine that keeps models honest, datasets clean, and on‑device demos grounded in good science.

Key responsibilities

• Curate and manage datasets
  • Gather and organize public scientific datasets (e.g., NASA/ESA archives, USGS) for imagery and spectra.
  • Clean and normalize metadata; track provenance and versions; enforce labeling conventions.
  • Create balanced train/validation/test splits and maintain a simple data catalog.
• Annotate and label scientific data
  • Use easy‑to‑learn tools (e.g., CVAT, Label Studio) to tag imagery (textures, microstructures) and spectral features.
  • Draft labeling guidelines, run spot‑checks for consistency, and calculate inter‑annotator agreement.
• Run and track experiments (no coding required)
  • Launch preconfigured workflows, notebooks, or GUI tools to run training/inference prepared by engineers.
  • Log hyperparameters, results, and observations; maintain tidy experiment trackers and dashboards.
• Edge hardware testing on Ambarella dev kits
  • Follow step‑by‑step guides to deploy prebuilt models on Ambarella SoCs.
  • Capture logs, FPS/latency, thermal and power readings; document test conditions and outcomes.
• Evaluate model performance and robustness
  • Build and maintain evaluation sets; compute and summarize metrics (precision/recall, confusion matrices).
  • Check for out‑of‑distribution behavior and data drift; flag failure cases with clear examples.
• Support field and lab data collection
  • Assist with camera/spectrometer operation following SOPs; capture calibration frames and maintain equipment logs.
  • Ensure data integrity, backups, and chain of custody for samples/files.
• Document and communicate
  • Write clear SOPs, labeling manuals, readme files, and experiment reports.
  • Summarize literature on biosignatures, spectroscopy, and relevant planetary science for the team.
  • Prepare slides and demos for internal reviews.

Required qualifications

• Pursuing a BS or MS in Biology, Astrobiology, Planetary Science, Geology, Chemistry, Physics, Data Science, or related field.
• Strong interest in astrobiology and applied AI at the edge.
• Comfortable working with spreadsheets (Excel/Google Sheets), organizing files and metadata, and handling CSVs.
• Excellent attention to detail; able to follow scientific SOPs and keep thorough notes.
• Clear written and verbal communication; proactive, organized, and collaborative.

Preferred skills

• Familiarity with basic statistics and evaluation concepts (averages, standard deviation, precision/recall).
• Exposure to spectroscopy or imaging (e.g., Raman/IR basics, hyperspectral imagery, microscopy).
• Experience with scientific data sources (e.g., NASA PDS) or formats (e.g., FITS, TIFF).
• Comfort using simple command‑line steps to run provided scripts or tools.
• Experience with annotation tools, photography/videography, or fieldwork logistics.