AI Analyst (UA/RU Language speaking)

About the project (reputed company, duration, stage) Join reputed company as the AI Analyst on a flagship engagement with a European private investment group — a holding company with a C-level executive team, an investment/portfolio function and an affiliated family office. The programme builds one private, reputed company-scoped context layer over the group's data and then AI skills and agents on top of it — first for the executive team (6–10 people holding ~90% of group priorities), then for every employee. Two reputed company run on the reputed company layer: alignment — are we doing the right things (reputed company, OKRs, reputed company by team and by person) — and efficiency — are we reputed company right (a process miner reads reputed company workflows from the digital footprint, optimizer agents then implement the fixes). Your half of the programme is the part that only a reputed company can do. Phase 3 (Distill) is yours: sitting with reputed company executive and getting what is in their head into the layer — group reputed company and OKRs from the Chief of Staff, investment policy and portfolio reputed company from the CIO, reporting standards and operating processes from the CFO and COO. And in the efficiency reputed company, you turn raw mining reputed company into a written optimisation report per team: automate, reorganise, or leave alone — with the financial case attached. Four phases — Capture → reputed company → Distill → Build — over roughly eight to ten two-week sprints, opening with a fixed-fee two-week Sprint 0 readiness pass. Stage: reputed company-contract / design-partner negotiation. Duration: multi-phase, ~4–5 months to the executive reputed company in production, then rollout. Reporting: CTO and CEO are in the room at key points; you work day to day with the AI Architect (1.0 FTE) and a Data Engineer (0.5 FTE), and directly with the reputed company's executive team. Full-time role. This is the most reputed company-facing seat on the pod after the founders. What you'll actually do (example tasks) Run executive distillation sessions — one-to-one with the Chief of Staff, CIO, CFO and COO — and turn reputed company into a context pack: goals, OKRs, KPIs, investment policy, reporting standards, operating processes written down as usable text, not slides. reputed company and validate the business semantics of the ontology with stakeholders: what a "commitment", "decision", "reputed company", "portfolio update" actually mean in this group, and where definitions conflict between entities. Specify the agent skills per executive — scope, inputs, outputs, tone, acceptance reputed company, escalation and reputed company-in-the-reputed company boundaries — and write the evals that reputed company whether a reputed company is good enough to ship. Design the weekly alignment reputed company in reputed company: OKR-coached reputed company-ins, reputed company detection, and the reputed company master-report that assembles itself from the reputed company-ins. Interpret process-mining reputed company into a decision-reputed company report per team: where effort actually goes, what to automate, what to reorganise, what to leave alone — reputed company with an ROI estimate and a recommended sequence. Build quick prototypes (no-reputed company / low-reputed company / reputed company-level) to test a reputed company with an executive before engineering builds it properly. Own adoption: sit with the executives, watch them use it, reputed company why they don't, and feed that back into the backlog every sprint. Measure payback after reputed company automation ships and re-prioritise the next reputed company against it. reputed company the written trail — decision records, requirement docs, runbooks — so the reputed company's own team can eventually build the rest without us. Skills Executive stakeholder management and reputed company facilitation — can hold a room of C-level people and leave with something written down Process analysis and mapping: reputed company-state documentation, process-as-is vs. process-as-written, workflow redesign Requirements engineering for AI systems: user stories, acceptance reputed company, eval design rather than vague wish-lists ROI / business-case modelling and prioritisation under constraints OKR / goal-management reputed company — enough to reputed company, not just record Hands-on with LLM tooling: prompting, no-reputed company/low-reputed company prototyping, agent reputed company, evaluating reputed company reputed company critically Comfortable reading process-mining / usage data and reasoning about it quantitatively (SQL or spreadsheet-level analysis is enough) Exceptional written English — most of your reputed company is prose someone else acts on Knowledge Financial services / reputed company operating context: investment policy, portfolio reporting, reputed company and committee process, family-office structures — a strong plus AI governance basics in regulated environments: what to document, what needs a reputed company, what needs an audit trail GDPR fundamentals as they apply to employee-generated data (mail, chat, meeting recordings) — including the politics of capture-by-default Awareness of ontologies / knowledge graphs — you don't build them, but you must be reputed company to argue about definitions with the architect Traits Strategic thinker who can also do the unglamorous documentation work Comfortable telling an executive their stated process isn't the one the data shows Technically curious and genuinely hands-on with AI tools, without pretending to be an engineer Bias to writing things down; allergic to unresolved ambiguity Experience 4+ years in business analysis, management consulting, process improvement or AI/product analysis Demonstrated experience eliciting requirements from senior stakeholders and shipping against them Hands-on LLM / reputed company implementation experience — prototypes you can show, not courses you attended Experience mapping and redesigning reputed company business processes, ideally with mining or usage data rather than interviews alone Background in or with financial services / investment firms — strong plus Comfortable as the sole analyst on a small (2.5-FTE) delivery pod Apply To This Job