Data Scientist

Overview

As Data Scientist at Viridien, you will transform raw data into structured, scalable datasets within our Data Hub, designing and maintaining data-processing pipelines. You will collaborate with domain experts and labeling teams, supporting annotation workflows and ML initiatives. You’ll work at the intersection of data engineering, domain knowledge, and machine learning to advance our data ecosystem and drive value for sustainability-focused challenges.

Pay / Benefits

• Competitive salary
• bonus scheme
• Hybrid model and flexible working with up to 2 days at home
• Initial 22 days annual leave with future increases
• Company pension with generous employer contribution
• Wellbeing Unmind app – mental health support

Responsibilities

• Develop data-transformation modules to gather, clean, validate, and structure raw datasets
• Collaborate with SMEs and labeling team to understand domain requirements
• Support annotation workflows with tools and technical feedback
• Build scalable, reusable data-processing solutions and manage version control with GitLab
• Troubleshoot data issues and flag inconsistencies or risks
• Maintain knowledge of the Data Hub tech stack and data schemas; stay current with tech trends
• Contribute to data integration, feature design, and machine learning initiatives
• Design and run experiments; document learnings and share results
• Use pre-trained ML models and train/fine-tune on internal datasets with evaluation and validation
• Communicate with team members and cross-functional partners to ensure alignment and transparency

Key requirements

• Background in data science or related field; Master’s degree preferred
• Proficient in at least one programming language, ideally Python, with experience in ML libraries
• Experience with hybrid ML workflows (traditional ML, LLMs, embeddings, ontologies, knowledge graphs)
• Comfortable with relational, NoSQL, and graph databases
• Strong data-processing skills including cleaning, filtering, and feature extraction
• Clear communicator with strong collaboration and presentation skills

• clear communicator
• strong collaboration
• presentation skills
• Python
• ML libraries
• hybrid ML workflows (traditional ML, LLMs, embeddings, ontologies, knowledge graphs)

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