This is a future role. We're building a shortlist now and will contact you when it opens.
About us
Foundational is building the most precise picture of Earth and orbit, using lasers fired from the ground. We call it ground truth for orbit.
We design and run low-cost, autonomous satellite laser ranging stations. They measure the distance to satellites with extreme precision, day and night. Our data platform turns those measurements into tracking data and orbit products for satellite operators, space agencies and governments. We also build our own flight-proven laser retroreflector arrays, so any satellite can be tracked.
Our station network is expanding across Europe, South America, Africa and Australia. The data supports resilient navigation, Earth observation and the safe, sustainable use of space.
We're a small, fast-moving team of engineers, scientists and operators in London. We're backed by venture investors and supported by ESA, the UK Space Agency, Innovate UK and the European Innovation Council.
Position Overview
London · Full time · On-site
You'll turn large volumes of laser ranging data into geodetic and orbit products at scale. You'll build the pipelines, models and quality checks behind them.
What you'll do
Build processing pipelines that take ranging data from raw returns to normal points and higher-level products
Develop statistical methods for bias detection, outlier rejection and data quality
Analyse station and network performance, and find where it can improve
Work with our geodesy and orbit determination team to turn research into products
Turn analysis into clear reports, plots and customer-facing metrics
What you'll bring
A degree in geodesy, physics, maths, data science or similar (MSc or PhD preferred)
Strong Python and the scientific stack (NumPy, pandas, SciPy)
Solid statistics: estimation, time series and uncertainty
Experience with large scientific datasets
A habit of writing production code, not just notebooks
Nice to have
SLR or GNSS data, including the CRD format
Cloud data pipelines
Machine learning for anomaly detection
What We Offer
A high-impact role with real ownership at an early-stage, venture-backed spacetech company
EMI share options (UK employees)
25 Days Annual Leave + Bank Holidays
Enhanced Parental Leave
Cycle to work schemes
Work alongside engineers and scientists across optics, lasers, software and astrodynamics
Offices in central London, with snacks, tea, coffee and regular socials
We actively champion underrepresented groups and seek to bridge gaps in our workforce. If you're excited by the role but don't match every point, or you’re seeking a part time role, please apply anyway and add a note into your application. Building the best team is our priority.
Skills Required
- Degree in geodesy, physics, mathematics, data science, or a similar field
- Strong Python skills and experience with NumPy, pandas, and SciPy
- Solid statistics knowledge, including estimation, time series, and uncertainty
- Experience with large scientific datasets
- Experience writing production code rather than only notebooks
- MSc or PhD
- SLR or GNSS data experience, including CRD format
- Cloud data pipeline experience
- Machine learning experience for anomaly detection
What We Do
We're an early-stage, mission-driven startup tackling one of the most exciting and complex challenges today to create the most precise understanding of space and earth using ground-based lasers. Using satellite laser ranging (SLR) data we are empowering the next generation of space companies with exquisite data that allows new forms of resilient navigation, earth observation and precise space traffic control - essential for the sustainability and resilience of the space domain, resilient navigation an the future of earth observation.
