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Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Build and scale Shield AI's corporate treasury: manage global cash positioning, liquidity forecasting, FX risk mitigation, banking relationships, debt covenant compliance, intercompany funding, and treasury controls while partnering with FP&A, Accounting, Legal, and Tax.
Aerospace • Artificial Intelligence • Machine Learning • Robotics • Software
Lead systems engineering for Hivemind-based autonomy products: define and manage requirements, develop system architectures and trade studies, coordinate hardware/software interfaces, support integration/verification/validation and testing, and identify and mitigate technical risks across the system lifecycle.
Top Skills:
C++Cameo ApiHivemind Autonomy SoftwareMbsePythonVelocity Template Language (Vtl)
Artificial Intelligence • Enterprise Web • Information Technology • Productivity • Sales • Software • Database
Own outbound net-new revenue in the mid-market (250–1000 employees). Proactively prospect 600+ accounts, engage Director+ and C-level buyers, run discovery/demos/negotiations, and close full-cycle deals with a data-driven, multi-threaded approach to meet quota and maintain accurate pipeline and forecasts.
The Company
Outrider is a software company that is automating distribution yards with electric, self-driving trucks. Our system eliminates manual tasks that are hazardous and repetitive while it improves safety and efficiency. Outrider’s mission is to drive the rapid adoption of sustainable freight transportation. We are a private company founded in 2018 and backed by NEA, 8VC, Koch Disruptive Technologies, NVIDIA, and other top-tier investors. Our customers are Fortune 200 companies and our autonomous trucks are already running in distribution yards. For more information, visit www.outrider.ai
OverviewWe are seeking a Data Analyst with strong SQL and Python skills to build, optimize, and support Streamlit dashboards and the data systems behind them. This role focuses on delivering reliable, performant analytics products by developing dashboards, improving underlying tables and pipelines, and ensuring data freshness and accuracy.
Key Responsibilities- Build and maintain Streamlit dashboards for business reporting and operational insights.
- Optimize dashboard performance (query tuning, caching strategies, efficient data loading, and rendering).
- Design, develop, and maintain SQL tables, views, and models that feed dashboards.
- Implement and maintain Python-based data workflows to transform, validate, and deliver data for analytics use cases.
- Monitor and improve data quality, freshness, and completeness (including automated checks and alerting).
- Partner with stakeholders to define metrics, ensure consistent definitions, and translate requirements into data products.
- Maintain documentation for dashboards, datasets, KPI definitions, and data lineage.
- Troubleshoot data and dashboard issues, providing timely support and root-cause analysis.
- Strong experience with SQL (complex joins, window functions, performance optimization, and data modeling).
- Strong experience with Python for data work (e.g., pandas, data validation patterns, and APIs as needed).
- Experience building dashboards using tools such as Streamlit (ideal), Looker, Tableau, etc.
- Solid understanding of analytics engineering fundamentals: dimensional modeling, metric definitions, and reproducible transformations.
- Knowledge of basic software engineering practices (Git workflows, code reviews, testing, CI/CD)
- Professional experience building dashboards in Streamlit, including performance tuning and maintainability.
- Familiarity with modern data stack concepts (ELT patterns, semantic layers, governance).
- Experience implementing automated data quality tests and observability.
- Experience working with large datasets and improving query and pipeline efficiency.
- Dashboards are fast, stable, and trusted by stakeholders.
- Underlying tables and transformations are efficient, well-documented, and easy to maintain.
- Data quality issues are detected early, with clear ownership and resolution paths.
- Metrics are consistent across dashboards and align with agreed business definitions.
- Strong analytical thinking and attention to detail.
- Ability to balance delivery speed with data correctness and maintainability.
- Clear written and verbal communication with technical and non-technical partners.
- Comfortable owning end-to-end analytics products from requirements to production support.
Assignment:
- 4-month contract with possibilities to extend
What you need to know about the Los Angeles Tech Scene
Los Angeles is a global leader in entertainment, so it’s no surprise that many of the biggest players in streaming, digital media and game development call the city home. But the city boasts plenty of non-entertainment innovation as well, with tech companies spanning verticals like AI, fintech, e-commerce and biotech. With major universities like Caltech, UCLA, USC and the nearby UC Irvine, the city has a steady supply of top-flight tech and engineering talent — not counting the graduates flocking to Los Angeles from across the world to enjoy its beaches, culture and year-round temperate climate.
Key Facts About Los Angeles Tech
- Number of Tech Workers: 375,800; 5.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Snap, Netflix, SpaceX, Disney, Google
- Key Industries: Artificial intelligence, adtech, media, software, game development
- Funding Landscape: $11.6 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Strong Ventures, Fifth Wall, Upfront Ventures, Mucker Capital, Kittyhawk Ventures
- Research Centers and Universities: California Institute of Technology, UCLA, University of Southern California, UC Irvine, Pepperdine, California Institute for Immunology and Immunotherapy, Center for Quantum Science and Engineering
