AI Analyst — Data Science Delivery
Indexed description
Adecco Romania
Our client is a leading supplier of information technology services and plays an essential role in global innovation.
With headquarters in Tokyo, it engages in commercial operations in more than 50 countries, with an emphasis on long-term commitment, and it combines a global reach with local availability, offering high-quality professional consulting services that range from systems development to integral outsourcing services.
Role Overview
The AI Analyst (Data Science Delivery) is an embedded technical practitioner within the AI & Data Science Delivery function, responsible for designing, building, and validating AI and ML solutions that power both the Productivity Squads (WS2) and Flagship Programme workstreams (WS3).
This is a hands-on delivery role requiring strong technical capability paired with the ability to communicate analytical outputs clearly to Finance stakeholders.
Work setup
Full remote (within Romania)
Collaboration type
B2B or CIM contract (initial period until the end of March 2027. Full-time engagement)
Start date: ASAP
Language: English (advanced)
Skills
- Strong Python skills (pandas, scikit-learn, PyTorch or similar); SQL proficiency essential
- Experience applying ML techniques to structured business data — classification, regression, anomaly detection, forecasting
- Familiarity with agentic AI patterns and LLM-based automation (prompt engineering, RAG, tool use) desirable
- Exposure to Finance data domains (GL, AP/AR, cost allocations, budgeting) a strong advantage
- Able to communicate technical outputs to non-technical Finance stakeholders with confidence
- Previous consultancy or in-house analytics delivery experience preferred
- Design and build machine learning models, statistical analyses, and AI-powered automations in response to shaped demand from the Product Lead
- Collaborate with Data Engineering (via UDP) to access, prepare, and quality-assure Finance data assets
- Deliver production-ready analytical solutions — from exploratory analysis to deployed model — within WS2 squad cycles (weeks, not quarters)
- Support WS3 Flagship workstreams with sub-function redesign analysis and the quantification of agentic automation opportunities
- Document model assumptions, lineage, and performance metrics to ensure auditability and Finance confidence
- Work with the AI Enablement team to embed outputs into Finance workflows and Copilot/AskV3-type tooling where appropriate
- Contribute to the development of reusable AI accelerators and playbooks across the programme
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