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Viridien (www.viridiengroup.com) is an advanced technology, digital and Earth data company that pushes the boundaries of science for a more prosperous and sustainable future. With our ingenuity, drive and deep curiosity we discover new insights, innovations, and solutions that efficiently and responsibly resolve complex natural resource, digital, energy transition and infrastructure challenges.
Job Details
We are seeking a Data Scientist to play a central role in transforming raw data into structured, reliable, and scalable datasets within our Data Hub environment. In this role, you will design and maintain data-processing pipelines, collaborate closely with domain experts and labeling teams, and contribute to machine learning initiatives that drive value across the organization.
This position offers the opportunity to work at the intersection of data engineering, domain knowledge, and machine learning—supporting innovative solutions while shaping our evolving data ecosystem.
Key Responsibilities
Develop systematic data-transformation modules to gather, clean, validate, and structure raw datasets. Collaborate closely with Subject Matter Experts (SMEs) and the labeling team, building a solid understanding of domain knowledge and requirements. Support SMEs and the labeling team by providing tools, solutions, and continuous technical feedback to improve annotation workflows. Build scalable, reusable data-processing solutions and maintain version control using GitLab. Troubleshoot and diagnose data issues, proactively flagging inconsistencies or risks. Maintain a deep understanding of the Data Hub technology stack and data schemas, staying current with emerging technologies, models, and research. Contribute to broader initiatives related to data integration, feature design, and machine learning. Design and run experiments, iterate based on results, and document and share learnings with the team. Use pre-trained ML models, and train or fine-tune models on internal datasets with proper evaluation and validation. Communicate regularly with team members, the team lead, and cross-functional partners in production and technology to ensure alignment and transparency.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Performance Metrics
Delivers high-quality work on time. Quickly learns and applies new tools, technologies, and concepts. Demonstrates strong understanding of Data Hub systems and workflows.
Qualifications & Skills
Background in data science or a related field (Master’s degree preferred). Proficient in at least one programming language—ideally Python—with experience in common ML libraries. Experience with hybrid ML workflows (traditional ML, LLMs, embeddings, ontologies, knowledge graphs). Comfortable working with relational, NoSQL, and graph databases. Strong data-processing skills, including cleaning, filtering, and feature extraction. Clear communicator with strong collaboration and presentation skills.
Why work with us?
Competitive salary commensurate with experience Highly attractive bonus scheme Hybrid model and flexible working with up to 2 days at home Initial 22 days annual leave with future increases, complemented by a flexible buying and selling holiday program Company pension with generous employer contribution Wellbeing Unmind app – puts you in control of your mental health A flexible benefits platform with numerous discount schemes - gym membership, restaurants, cinema tickets, and much more! Regular social club events, spontaneous reward events throughout the year Cycle purchase scheme Flexible Private Medical & Dental care programmes Sponsorship of visas/comprehensive relocation packages Bank Holiday Swap - our holiday swap program allows you to change it for another day of your choice! Relaxed dress code policy


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Our Hiring Process
At Viridien, we are committed to delivering a respectful, inclusive, and transparent recruitment experience.
Due to the high volume of applications we receive, we may not be able to provide individual feedback to every applicant. Only candidates whose qualifications closely match the role criteria will be contacted for an interview. We do, however, aim to share personalized feedback with those who progress to the first round of interviews and beyond.
We are also dedicated to ensuring that our hiring process accessible to all. If you require any reasonable adjustments to fully participate in the application or interview stages, please don’t hesitate to contact your recruiter directly.
We see things differently. Diversity fuels our innovation, we value the unique ways in which we differ, and we are committed to equal employment opportunities for all professionals.
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