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Superbet is seeking a Staff Strategy & Competitive Intelligence Researcher to weave user evidence into strategic decisions across markets, competitors, and regulatory landscapes. You own an always-on intelligence system that synthesises signals from research, market data, and policy developments to inform executive choices.
In this role you will operate inside the research function while engaging with board prep, regulator conversations, and strategic capital allocation, guiding decisions with a
Most strategy work in large gaming organisations lives in finance decks and consulting reports. It is slow, expensive, and disconnected from the user evidence the research function spends its life generating. This role exists to close that gap.
As Staff Strategy & Competitive Intelligence Researcher at Superbet, you are the person who connects what we know about users to what we decide about markets, competitors, and bets. You own the intelligence layer that sits above the existing research stack — taking the consumer signal from User Research, the behavioural signal from Quant Research, and the campaign-level competitive signal from Market Intelligence, and turning it into a continuous, opinionated strategic view that the CEO, CPO, CMO, and Board can act on.
Concretely, this means: when leadership is debating whether to enter a new geography, you produce the TAM/SAM/SOM, the competitor heat map, the regulatory readiness assessment, and a clear recommendation — in three weeks, not three months. When a competitor announces a major product or M&A move, you have a synthesised interpretation in front of the executive team within 48 hours, not next quarter's strategy review. When a regulator in one of our 12+ markets signals a policy shift, you flag the commercial implication before our competitors have written their first memo on it.
You do not run agency studies or commission McKinsey decks to answer these questions. You operate an AI-native intelligence system that does it continuously, at a fraction of the cost, and with stronger first-party grounding than any external firm can offer. You are the in-house equivalent of a QuantumBlack engagement — but always-on, embedded, and aligned to Superbet's specific commercial reality.
You sit inside the Research function but spend a significant share of your time outside it: in commercial reviews, in regulator conversations, in board-prep sessions, and in the rooms where strategic capital is allocated. Your job is not to produce a report. It is to change a decision.
Strategy as a continuous system, not a quarterly artefact. You do not build strategy decks on demand. You operate a live competitive and market intelligence system that updates itself — pulling competitor product releases, financial filings, ad spend signals, regulator publications, and market data into a synthesised, AI-summarised feed that you interpret and act on weekly.
Market sizing as code, not as a one-off Excel. Your TAM/SAM/SOM models are versioned, parameterised, and re-runnable. When the gambling tax changes in Romania, when a competitor enters Brazil, when a regulator caps stakes in the Netherlands — the model updates and the implication is in front of leadership the same day. You build this infrastructure yourself; you do not wait for finance.
LLMs as a synthesis layer over thousands of unstructured strategic signals. Competitor earnings transcripts, regulator consultation responses, industry analyst notes, press releases, executive LinkedIn activity, app store updates, sportsbook pricing data — all of this is now machine-readable. You design the pipelines that surface what matters, validate the outputs critically, and feed the synthesised view into executive decisions.
Synthetic stress-testing before expensive bets. Before recommending a major strategic move, you run AI-driven scenario simulations: how would this play out in three plausible regulatory futures, against two distinct competitor response patterns, across our five highest-value markets? You use this to surface fragility in a strategy before it gets greenlit.
Critical AI judgement as a core skill. You know exactly where AI-generated strategic analysis fails: confirmation bias in prompt design, hallucinated market data, over-confident competitor inferences from sparse signal, narrative compression that loses the decisive nuance. You build validation steps into every workflow and you can defend the methodology to a sceptical CFO.