National AI Awards 2025Discover AI's trailblazers! Join us to celebrate innovation and nominate industry leaders.

Nominate & Attend

SDA Orbital Analyst

People Source Consulting Ltd trading as Experis
Farnborough
6 months ago
Applications closed

Role: SDA (Space Domain Awareness) Orbital Analyst

Located: Farnborough

Onsite: 2 or 3 days per week

Salary: £ is depending on experience they aim to be competitive




Responsibilities:


We are currently seeking an SDA Orbital Analyst, to play a key role in monitoring, analysing, and predicting the behaviour of space objects. In this role you will develop and use analytical tools and processes to produce timely, high-quality data sets and products for military, civil and commercial decision-makers.



You will collaborate closely with our multidisciplinary team of hardware and software engineers to develop SDA capabilities to meet the evolving demands of international space markets. You will also help to shape the SDA strategy; participate in proposal development; and create technical SDA solutions to meet key customer requirements.




  • Planning, scheduling, and executing SDA sensor taskings to optimize the collection of relevant data.
  • Interpreting, analysing, and fusing multi-source SDA data, from both space-based and ground based RF and optical systems.
  • Developing decision-quality data products within operationally relevant timescales to meet customer requirements.
  • Developing new analytical tools and/or processes to maximise the potential of GES sensor and data platform capabilities.
  • Engaging with existing and potential customers to tailor SDA solutions to their needs.
  • Providing technical SDA advice to the business development and marketing teams.
  • Monitoring relevant SDA marketplaces and uploading product offerings.
  • Providing technical consulting services in support of projects, programmes, and operational experimentation.
  • Authoring technical documentation in support of bid proposals, consulting projects and product validation.
  • Providing technical presentations and advice the Board and Senior Management Team when required.






Experience needed:


  • Minimum of 2+ years professional experience in Space Surveillance and Tracking (SST), Space Domain Awareness (SDA) and/or space system operations with a comprehensive understanding of SDA, Space Weather, and SST modelling and analysis.
  • A bachelor’s degree, ideally in a relevant field
  • A comprehensive understanding of orbital mechanics, astrodynamics, and atmospheric physics.
  • Broad understanding and experience in data analysis and analytical software utilisation including experience in the development of automated scripts and/or simple software products. Working knowledge of data mining, data analysis and data visualization tools.
  • Skilled in the one or more of the following programming languages: Fortran, C/C++, Java, Matlab, Python, SQL, Javascript.
  • Excellent communication skills
  • An understanding of IT systems and proficient in the use of Microsoft Office applications.
  • Able to hold SC security clearance.




Desirable:


Professional experience in the space industry or related field (e.g. RF engineering or radar development).




Benefits:


  • Holiday - 25 days plus bank holidays
  • Life Assurance
  • Private Medical Cover
  • Private Dental Cover
  • Company Pension Scheme
  • Enhanced Maternity & Paternity Cover




How to apply?


Please send a CV to

National AI Awards 2025

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Return-to-Work Pathways: Relaunch Your Machine Learning Career with Returnships, Flexible & Hybrid Roles

Returning to work after an extended break can feel like starting from scratch—especially in a specialist field like machine learning. Whether you paused your career for parenting, caring responsibilities or another life chapter, the UK’s machine learning sector now offers a variety of return-to-work pathways. From structured returnships to flexible and hybrid roles, these programmes recognise the transferable skills and resilience you’ve developed, pairing you with mentorship, upskilling and supportive networks to ease your transition back. In this guide, you’ll discover how to: Understand the current demand for machine learning talent in the UK Leverage your organisational, communication and analytical skills in ML contexts Overcome common re-entry challenges with practical solutions Refresh your technical knowledge through targeted learning Access returnship and re-entry programmes tailored to machine learning Find roles that fit around family commitments—whether flexible, hybrid or full-time Balance your career relaunch with caring responsibilities Master applications, interviews and networking specific to ML Learn from inspiring returner success stories Get answers to common questions in our FAQ section Whether you aim to return as an ML engineer, research scientist, MLOps specialist or data scientist with an ML focus, this article will map out the steps and resources you need to reignite your machine learning career.

LinkedIn Profile Checklist for Machine Learning Jobs: 10 Tweaks to Drive Recruiter Interest

The machine learning landscape is rapidly evolving, with demand soaring for experts in modelling, algorithm tuning and data-driven insights. Recruiters hunt for candidates proficient in Python, TensorFlow, PyTorch and MLOps processes. A generic profile simply won’t cut it. Our step-by-step LinkedIn for machine learning jobs checklist covers 10 targeted tweaks to ensure your profile ranks in searches and communicates your technical impact. Whether launching your ML career or seeking leadership roles, these optimisations will sharpen your professional narrative and boost recruiter engagement.

Part-Time Study Routes That Lead to Machine Learning Jobs: Evening Courses, Bootcamps & Online Masters

Machine learning—a subset of artificial intelligence—enables computers to learn from data and improve over time without explicit programming. From predictive maintenance in manufacturing to recommendation engines in e-commerce and diagnostic tools in healthcare, machine learning (ML) underpins many of today’s most innovative applications. In the UK, demand for ML professionals—engineers, data scientists, research scientists and ML operations specialists—is growing rapidly, with roles projected to increase by over 50% in the next five years. However, many aspiring ML practitioners cannot step away from work or personal commitments for full-time study. Thankfully, a rich ecosystem of part-time learning pathways—Evening Courses, Intensive Bootcamps and Flexible Online Master’s Programmes—empowers you to learn machine learning while working. This comprehensive guide examines each route: foundational CPD units, immersive bootcamps, accredited online MSc programmes, funding options, planning strategies and a real-world case study. Whether you’re a software developer branching into ML, a statistician aiming to upskill, or a professional exploring AI-driven innovation, you’ll discover how to build in-demand ML expertise on your own schedule.