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Raytheon Technologies Data Science & Machine Learning Research Engineer in Gloucester, United Kingdom

What is Raytheon’s Strategic Research Group (SRG)?

Part of Raytheon UK’s Cyber and Intelligence (C&I) business, the Strategic Research Group (SRG) is a multi-disciplinary expert team focused on next-gen research in artificial intelligence, security research and cloud technology.

SRG is not yet another software team building enterprise solutions.

The group operate at the cutting edge of technology and research, applying world class research to customer-relevant challenges in order to create unique prototypes, genuine expertise and valuable hands-on skills.

Established in Jan 2019, SRG was created to focus Raytheon’s efforts on next-generation technologies critical to create the future capabilities our customers demand.

In the short time since the group was established, greats success - both technically and commercially - has been achieved.

As a result of these successes, SRG is seeking to grow, allowing the group to tackle more challenges and deliver further successes.

What makes SRG different?

SRG is an expert group, made of a team of people with broad skills, expertise and experience.

The team includes post-doctorate researchers, experienced data scientists and engineers with customer knowledge, security research and machine learning expertise.

SRG’s culture sets it apart from many other teams.

It is vital to how the group operates and to its success.

SRG values creating and sharing tangible results over creating overly detailed plans and excessive PowerPoint presentations.

The team deliver a mix of internally funded research and customer funded projects.

SRG work on a ‘cloud first’ basis - AWS, Atlassian, GitHub, Slack are main productivity tools.

SRG is collaborative, supportive and independent.

Above all, every member of the group strives to delight and impress our stakeholders, taking great pride in their work.

Data Science & Machine Learning Research Engineer

Location - Gloucester

Essential Behaviours & Attitude

Delivery .

Hands-on experience designing, creating, building and operating complex software systems.

Strong experience with modern software engineering approaches and best practices.

Effective Communicator .

Able to tailor written and verbal communication to a wide range of audiences including technical authors, customers, conferences and public events.

Successful examples of conference speaking, customer engagement and managerial presentations.

Inquisitive self-starter .

Work with autonomy, able to build trusted relationships and rapidly establish a reputation for enthusiasm, delivery and reliability.

Supportive and collaborative .

Must be able to demonstrate clear examples of providing support to team members and colleagues

Track record of creating a collaborative working ethos within a team or organisation.

Resilient and driven .

Must be able to stay goal focused, regardless of blockers, obstacles or wider issues both in personal work and within the wider team.

Willingness to learn and work across boundaries .

Ability to work in new disciplines as a non-expert within expert teams is essential.

Willingness and energy to learn new topics, new concepts and new skills in order to facilitate collaboration and solve problems.

Core Technical Skills

We expect:

Solid technical and research foundation, either academic or professional track record in technology, research and early-stage development.

Strong knowledge of core machine learning models, algorithms and techniques.

Good skills - or demonstrable ability to rapidly learn - standard data science toolset including Python, sckitlearn, Jupyter, Apache Spark and the wider Hadoop eco-system

Your professional achievements must demonstrate:

Track record rapidly creating early-stage prototypes under uncertainty

Proven ability to create software artefacts using modern software engineering best practices where appropriate

Broader Experience

SRG welcomes individuals with a broad range of experiences, diverse careers and technical qualifications.

Such diversity of thought is an asset, and as such, broad career experience is valuable:

Professional certification in AWS Machine Learning or Solutions Architecture, Cloudera Data Scientist or other technologies.

Specialist knowledge in automated reasoning, computer vision, natural language understanding, predictive analytics, behavioural analytics or any other applied machine learning domain

Experience creating and deploying production-grade machine learning workloads in a Hadoop eco-system (either on-prem or public cloud)

Experience working in the Defence and National Security domain, in particular direct experience working with UK Government customers.

Evidence of proactive self-development and self-directed learning in particular Kaggle participation

Research credentials, either academic or professional, to evidence ability to innovate and contribute new results to the scientific literature.

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