• Bridge the gap between complex datasets and strategic action. • Synthesize information from various external sources to develop visibility and insights into search recall gaps and emerging topic trends. • Inform Wikimedia’s strategy for ensuring that people continue to find the content they need. • Integrate fragmented data to create a unified view of how users discover and use content. • Translate analytics and complex trends into actionable narratives. • Develop automated systems to detect under-indexed content. • Establish metrics and frameworks for content utilization within Large Language Models. • Collaborate with product leaders to set goals and track success. • Assess efficacy of new initiatives through experiment design and analysis • Interpret website performance data to inform UX/UI enhancements.

• Design, prepare data and conduct analysis and delivery of RWE analyses for biopharma clients. • Generate insights from complex real-world endpoints using extensive coding, demonstrating deep comprehension of Natera clinical and molecular data structures and complexity. • Build technical standards by implementing advanced methods in survival analysis, machine learning and predictive modeling. • Integrate practical adoption of Natera tools including: LLMs and agentic tools into your own daily workflow. • Own the communication of high impact/value results to internal stakeholders and external partners. • Collaborate with internal product, oncology, and clinical abstraction, medical, scientific, business development and consortia teams to continually enhance Natera data quality, products, and analytical best practices. • Proactively identify gaps in current products and ensure that customer feedback is collected and integrated into the Natera product road map. • Maintain deep expertise in oncology clinical guidelines (e.g., NCCN) and emerging RWE methodologies.

• Strategy Execution: Lead on data strategy execution, leading by example in a hands-on capacity • Data Foundations: Design and create the single source of truth for critical business entities and implement processes to ensure the business builds on solid data foundations • Data Products: Develop data products that allow for controlled, self-service data access • Leadership: Lead and mentor the data team, fostering a culture of high performance and innovation • Governance & Quality: Own data quality and governance in an FCA-regulated environment, ensuring accurate audit trails • Cross-Functional Collaboration: Work closely with the Salesforce team to own Salesforce data models and ensure holistic governance • Technical Alignment: Work with the VP of Engineering to ensure alignment with the wider technical strategy and business objectives.

Role Description We are seeking a distinguished Visiting Staff Scientist to join our AI Research (AIR) team for a one-year sabbatical residency. In this role, you will play a pivotal part in our mission to create a “Queryable Earth” by leading the development of Planet’s proprietary geospatial foundation models (GFMs). - Lead the research and development of a foundation model specifically trained on Planet imagery, incorporating the time-axis to create high-cadence time-series embeddings. - Systematically evaluate and compare existing GFMs (e.g., TerraMind, Prithvi, Clay) against PlanetScope data to assess performance, computational cost, and transferability. - Design embeddings and workflows optimized for detecting short-lived, high-impact events such as floods, rapid surface-water expansion, and fire. - Explore the synergy between PlanetScope, Sentinel-1 SAR, and other commercial SAR data to ensure robust time-series analysis even under cloud cover. - Use embeddings to design active learning workflows that prioritize labeling and reduce the annotation burden for time-sensitive mapping tasks. - Publish findings in top-tier journals and present at conferences (e.g., IGARSS, CVPR), highlighting PlanetScope’s unique value in the foundation model ecosystem. - Oversee the technical direction of a dedicated postdoc and collaborate with Planet’s research scientists to transition prototypes into operational products. Qualifications - PhD and current Faculty/Professor status in Geospatial Analytics, Computer Science, Remote Sensing, or a related field. - 12+ years of experience in remote sensing and satellite image analysis, with a proven track record in building AI-based models for environmental change (e.g., flood-extent, water dynamics). - Extensive experience with foundation models, contrastive learning (CLIP-like models), and multi-model vision-language models (MMVLMs). - Proficiency in multi-sensor integration (Landsat, Sentinel-2, PlanetScope, Sentinel-1) and high-resolution mapping at varying scales (3m, 10m, 30m). - Expert-level Python skills and experience with the scientific stack (xarray, Dask, NumPy, Rasterio, GeoPandas) and deep learning frameworks. - Experience building automated pipelines for preprocessing and labeling planetary-scale datasets. - A history of leading research labs and a desire to work in a fast-paced, industrial R&D environment. Requirements - Extensive experience specifically in flood damage quantification and methane-related water dynamics. - History of leading NASA-funded or similar high-impact geospatial research projects. - Direct experience fine-tuning or modifying specific GFM architectures like TerraMind or Prithvi. - A mix of deep academic rigor and the ability to prototype rapid-change monitoring tools for operational readiness. Benefits - Comprehensive Medical, Dental, and Vision plans - Health Savings Account (HSA) with a company contribution - Generous Paid Time Off in addition to holidays and company-wide days off - 16 Weeks of Paid Parental Leave - Wellness Program and Employee Assistance Program (EAP) - Home Office Reimbursement - Monthly Phone and Internet Reimbursement - Tuition Reimbursement and access to LinkedIn Learning - Equity - Commuter Benefits (if local to an office) - Volunteering Paid Time Off