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Senior Applied Scientist, Knowledge Graphs and ML(m/w/x)
Description
In this role, you will drive innovation by designing experiments and exploring cutting-edge techniques in knowledge graphs and machine learning. Your work will directly impact the development of risk and fraud investigation software, ensuring that solutions meet both scientific and business needs.
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Requirements
- •PhD in a relevant discipline or Master's plus comparable research experience
- •Hands-on industry experience building NLP, ML, Knowledge Graph, or GenAI systems
- •Experience investigating knowledge graph design and construction
- •Deep knowledge of modern NLP methods and GenAI techniques
- •Experience writing production code and managing software delivery
- •Experience translating complex problems into successful AI applications
- •Outstanding communication, problem-solving, and analysis skills
- •Collaboration with Product, Engineering, and Business Stakeholders in an agile manner
- •Experience working with real-world, messy data in commercial contexts
- •Excellent coding skills in Python, proficiency with Git and cloud technologies
Education
Work Experience
approx. 4 - 6 years
Tasks
- •Design and execute experiments to answer critical research questions
- •Explore graph ML, RAG architectures, and agentic AI
- •Test new algorithms and techniques for value delivery
- •Manage end-to-end knowledge graph experimentation and development
- •Guide research, data engineering, and evaluation efforts
- •Operate in an agile manner, focusing on quick iterations
- •Account for all research deliverables on small to medium-sized projects
- •Collaborate with stakeholders to define project scope and feasibility
- •Translate business objectives into technical requirements
- •Partner with Engineering for effective software delivery
- •Co-design ML Ops processes
- •Mentor junior scientists on knowledge graph best practices and NLP techniques
Tools & Technologies
Languages
English – Business Fluent
Benefits
Flexible Working
- •Flexible hybrid working environment
Workation & Sabbatical
- •Work from anywhere for up to 8 weeks
Learning & Development
- •Continuous learning and skill development
More Vacation Days
- •Flexible vacation
Mental Health Support
- •Two company-wide Mental Health Days off
- •Access to the Headspace app
- •Resources for mental, physical, and financial wellbeing
Retirement Plans
- •Retirement savings
Additional Allowances
- •Tuition reimbursement
Bonuses & Incentives
- •Employee incentive programs
Social Impact
- •Two paid volunteer days off annually
- •Opportunities for pro-bono consulting projects
Sustainability Focus
- •Environmental, Social, and Governance initiatives
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Senior Applied Scientist, Knowledge Graphs and ML(m/w/x)
The AI Job Search Engine
Description
In this role, you will drive innovation by designing experiments and exploring cutting-edge techniques in knowledge graphs and machine learning. Your work will directly impact the development of risk and fraud investigation software, ensuring that solutions meet both scientific and business needs.
Let AI find the perfect jobs for you!
Upload your CV and Nejo AI will find matching job offers for you.
Requirements
- •PhD in a relevant discipline or Master's plus comparable research experience
- •Hands-on industry experience building NLP, ML, Knowledge Graph, or GenAI systems
- •Experience investigating knowledge graph design and construction
- •Deep knowledge of modern NLP methods and GenAI techniques
- •Experience writing production code and managing software delivery
- •Experience translating complex problems into successful AI applications
- •Outstanding communication, problem-solving, and analysis skills
- •Collaboration with Product, Engineering, and Business Stakeholders in an agile manner
- •Experience working with real-world, messy data in commercial contexts
- •Excellent coding skills in Python, proficiency with Git and cloud technologies
Education
Work Experience
approx. 4 - 6 years
Tasks
- •Design and execute experiments to answer critical research questions
- •Explore graph ML, RAG architectures, and agentic AI
- •Test new algorithms and techniques for value delivery
- •Manage end-to-end knowledge graph experimentation and development
- •Guide research, data engineering, and evaluation efforts
- •Operate in an agile manner, focusing on quick iterations
- •Account for all research deliverables on small to medium-sized projects
- •Collaborate with stakeholders to define project scope and feasibility
- •Translate business objectives into technical requirements
- •Partner with Engineering for effective software delivery
- •Co-design ML Ops processes
- •Mentor junior scientists on knowledge graph best practices and NLP techniques
Tools & Technologies
Languages
English – Business Fluent
Benefits
Flexible Working
- •Flexible hybrid working environment
Workation & Sabbatical
- •Work from anywhere for up to 8 weeks
Learning & Development
- •Continuous learning and skill development
More Vacation Days
- •Flexible vacation
Mental Health Support
- •Two company-wide Mental Health Days off
- •Access to the Headspace app
- •Resources for mental, physical, and financial wellbeing
Retirement Plans
- •Retirement savings
Additional Allowances
- •Tuition reimbursement
Bonuses & Incentives
- •Employee incentive programs
Social Impact
- •Two paid volunteer days off annually
- •Opportunities for pro-bono consulting projects
Sustainability Focus
- •Environmental, Social, and Governance initiatives
About the Company
Thomson Reuters
Industry
FinancialServices
Description
The company provides trusted content and technology for professionals in legal, tax, accounting, compliance, government, and media.
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