Data Scientist and Innovation Manager

at  Spektrum

Spektrum have a wide range of exciting opportunities in several global locations.
We are always looking to add great new talent to our team and look forward to hearing from you.
Spektrum supports apex purchasers (NATO, UN, EU, and National Government and Defence) and their Tier 1 supplier ecosystem with a wide range of specialist services. We provide our clients with professional services, specialised aerospace and defence sales, delivery, and operational subject matter expertise. We are looking for personnel to join our team and support key client projects.

WHO WE ARE SUPPORTING

The Joint Analysis and Lessons Learned Centre (JALLC) is a NATO entity located in Lisbon, Portugal. The Joint Analysis and Lessons Learned Centre (JALLC) is involved in a wide range of activities:

• Analysis – The JALLC conducts three types of analysis in support of its mission: Joint Analysis of NATO-wide complex issues, Short Term Analysis of issues with strategic implications that require a swift response, and NATO Lessons Learned Portal Content Analysis of Lessons Learned information and trends on the NLLP. Each type of analysis is conducted by civilian and military subject matter experts as appropriate who, besides their own education and experience, undergo the JALLC Analyst Training Course when they join the JALLC to ensure a seamless service across the JALLC’s analysis activities.
• Lessons Learned - The JALLC facilitates Lessons Learned in NATO through its various Lessons Learned activities. These activities include managing the NATO Lessons Learned Portal, providing assessment and advice on the implementation of the NATO Lessons Learned Capability, analysing the content of the NATO Lessons Learned Portal identifying trends and themes, and providing Lessons Learned training to NATO entities, Member Nations, and Partner Nations whether in the classroom, on site, or virtually. Additionally, the JALLC provides support to the NATO Lessons Learned community more generally in the form of the NATO Lessons Learned events, including the NATO Lessons Learned Conference which covers topical themes and draw participants from all over NATO and beyond.
• Training - The JALLC provides a series of training courses for both internal and external participants. Courses objectives range from training in analysis techniques and project management to basic training in Lessons Learned for Lessons Learned Staff Officers and Points of Contact. All of the JALLC’s training courses are reviewed and revised regularly based on participant feedback to ensure the best possible training experience
• Support to Exercises and Operations - The JALLC’s support to exercises is multi-faceted and underpins all aspects of the JALLC Mission. The JALLC’s Exercise Support team and military and civilian analysts participate in all stages of the NATO Exercise Process, from Exercise Specification and Development, through Planning and Product Development, Operational Conduct to Analysis and Reporting. The JALLC provides support to operations by facilitating Lessons Learned training, Active Content Management of the NATO Lessons Learned Portal, and Joint Analysis. This support is tasked as required and includes support to operations in the form of support to Operational Plans, Key Leader Training and Subject Matter Expert support for planning conferences.

The program Under the JALLC’s strategic objective “Anchored to the Future”, and the JALLC Innovation Framework Standard Operating Procedure, the JALLC runs an annual innovation plan consisting of a number of innovation projects intended to prepare JALLC for NATO 2030. A nominated innovation facilitator is responsible for managing the implementation of the innovation plan, and nominated JALLC staff are responsible to lead and contribute to the innovation projects. However, the JALLC staff currently performing these duties are doing so in addition to the full-time duties of their permanent positions. As a consequence, there is a risk that JALLC will not be able to complete its Innovation Plan 2024, and JALLC’s ability to ensure its innovation efforts remain coherent and harmonized with NATO’s wider 2030 activities, is seriously constrained. Additionally, some of JALLC’s innovation projects require skillsets that do not exist in the JALLC peacetime establishment.

Commander JALLC approved the JALLC Innovation Plan 2024 containing five innovation projects as follows:

• JALLC AI-enabled Research Tool (J-ART): Objective(s): Enable JALLC analysts to process large unstructured natural language data sets in a systematic and repeatable manner. Automate routine analysis tasks.
• JALLC Editorial Enhancement Project (JEEP): Objective(s): Develop prototype new JALLC report template(s) incorporating automation and/or interactivity. Automate routine editorial tasks.
• JALLC Online Guides (JOG): Objective(s): Develop prototypes for online interactive versions of the NATO LL Handbook and JALLC Analysis Handbook.
• Innovation Transfer & Training (ITT): Objective(s): Develop knowledge and culture of innovation at JALLC.
• Semantic Representation for NATO Exploitation of LL (SERENE): Objective(s): Represent NATO and the JALLC’s interests in the multinational NATO Science and Technology Organization (STO). project SAS-IST-179 Research Task Group (RTG) on Semantic Representation to Enhance Exploitation of Military Lessons Learned.

DESIRABLE SKILLS AND EXPERIENCE

• NATO/Military Awareness: Broad knowledge and understanding of NATO’s military activities gained through study or experience.
• Knowledge Management/Lessons Learned Knowledge. Broad knowledge and understanding of the fields of Knowledge Management or Lessons Learned gained through study or experience.
• Agile Methodology: Agile methodology certification or experience.
• Research Skills. Study of research design/methodology and completion of an independent research project (thesis/dissertation) (e.g. as part of a research-based Masters or PhD course).

EDUCATION

• University degree in computer science, linguistics, economics, statistics, operations research, or related discipline.

Essential Skills and Experience

• Data Science Experience. Four years’ experience working as a data scientist, data analyst, or similar role, with a focus on natural language processing and semantics problems.
• Model Building and Deployment Experience. Experience in building and deploying models for natural language processing and machine learning including experience working with SQL databases, vectorization, knowledge graphs, large/small language models (LLM/SLM), Retrieval Augmented Generation (RAG), and Python.
• Project Management. Experience managing small projects.
• Communication and Collaboration. Strong communication and collaboration skills, including the ability to translate technical findings to non-technical stakeholders and work effectively in cross-functional teams. Experience of report writing in English for non-technical audiences

ROLE BACKGROUND

The ambitious Innovation Plan is necessary to prepare JALLC for NATO 2030. However it is currently being entirely delivered by JALLC staff alongside their full-time duties. This means that it is suffering delays due to competing priorities. In particular, the Principal/Senior Operational Research Analysts and Editor, who are leading most of the work, are facing an additional burden of covering a gap caused by two civilian research analyst vacancies in JALLC during the second semester 2024. This means there is significant risk that the Innovation Plan will not be delivered on time. Additionally, in the early days of the J-ART and SERENE projects, it has become apparent that the technical knowledge and experience of the JALLC staff is insufficient to complete the
projects to a satisfactory standard. The JALLC Lessons Learned Analysis Division (LLAD) therefore requires contractor support for specialist skills and capacity reasons to deliver the tasks and deliverables described below.

ROLE DUTIES AND RESPONSIBILITIES

• Proactively, and with minimal supervision, to use the knowledge and experience to plan, conduct, and lead assigned tasks and deliverables.
• Bring a blend of data science/AI technical skills and innovation management skills.
• Use specialised programming techniques to develop and apply data science, natural language processing, and AI techniques and models to new problems and large and varied sets of unstructured text contributing to the Digital Transformation of the JALLC and NATO 2030.
• Support and facilitate JALLC’s annual cycle of innovation project planning.
• Manage, monitor and report on the implementation of the JALLC Innovation Plan.
• Use SQL, vector/graph databases, RAG, and Python, to improve performance of LLMs for JALLC tasks.
• Lead or contribute to writing technical reports/conference papers, and their peer review and revision process.
• Provide subject matter expertise to (military and civilian) staff within the JALLC and develop proofs of concept, as directed.
• Support educational efforts and training development related to NATO Enterprise data, AI or digital literacy.
• Remain up-to-date with new developments in data science, natural language processing, and AI to bring innovative ideas into implementation for JALLC.
• Collaborate with other data professionals, software engineers and subject matter experts from different functional areas and the NATO Enterprise.
• Support the Innovation Facilitator by leading or contributing to the delivery of the JALLC’s Innovation Plan and associated Innovation Project deliverables:
• Technical Report on JALLC’s agile development of a LLM-based AI-enabled research tool in the NATO SANDI development environment. (Due Oct 2024)
• Conference Paper on JALLC’s development in the NATO SANDI. (Due Feb 2025)
• Innovation Updates in JALLC Monthly Reports and the JALLC Annual Innovation Plan Report. (Due Dec 2024)
• Paper on Granularity and Abstraction of Lessons Learned as Knowledge Artefacts (Due Dec 2024)

• Other similar or related tasks or deliverables.

  Essential Skills and Experience

• Data Science Experience. Four years’ experience working as a data scientist, data analyst, or similar role, with a focus on natural language processing and semantics problems.

• Model Building and Deployment Experience. Experience in building and deploying models for natural language processing and machine learning including experience working with SQL databases, vectorization, knowledge graphs, large/small language models (LLM/SLM), Retrieval Augmented Generation (RAG), and Python.
• Project Management. Experience managing small projects.
• Communication and Collaboration. Strong communication and collaboration skills, including the ability to translate technical findings to non-technical stakeholders and work effectively in cross-functional teams. Experience of report writing in English for non-technical audiences.