MrQ is an award‑winning online casino launched in 2018 that values technology, performance, and fun.
We are rapidly growing and are looking for rock stars to join our quest for world domination.
MrQ is seeking an experienced Data Scientist to join our Revenue Operations team. RevOps is the architect of the company’s revenue engine and uses mathematics, statistics, data, and machine learning to protect, predict, and maximize revenue. This role has direct exposure to commercial programmes across every part of the business.
What You Will Do
* Causal Inference & Explainability
o Design and deploy causal inference frameworks to explain metric movements across acquisition, retention, and revenue, moving the business beyond correlation to confident causal attribution.
o Build automated decomposition models that identify why a KPI has shifted (e.g. mix effects, seasonality, campaign impact, product changes) and surface actionable root causes to stakeholders.
o Partner with teams to embed causal thinking into decision‑making workflows—replacing gut feel with evidence‑backed direction.
* Agentic AI & Always‑On Insight
o Using the inference frameworks, architect and build specialised AI agents that autonomously monitor key business metrics, detect anomalies, and generate natural language explanations.
o Develop agent systems that combine metric surveillance, contextual awareness, and LLM‑powered explainability—so insight is proactive, not reactive.
o Ensure agents are robust, well‑validated, and capable of handling the complexity of the business.
o Continuously improve agent intelligence over time by incorporating new data signals, feedback loops, and evolving business context.
What We’re Looking For
* Master’s degree (or PhD) in Data Science, Statistics, Mathematics, or a related field.
* 5+ years of applied data science experience, ideally in digital, gaming, gambling, or another high‑growth consumer‑facing industry.
* Expertise in causal inference methods—uplift modelling, difference‑in‑differences, instrumental variables, and causal ML frameworks (e.g. DoWhy, EconML).
* Hands‑on experience designing and building AI agents or agentic pipelines, including tool use, orchestration, and LLM integration.
* Expert knowledge of R or Python for statistical modelling and machine learning.
* Excellent SQL skills for querying and transforming large datasets.
* Strong communication skills and proven experience influencing senior stakeholders.
Success Looks Like
In 3 Months
* Develop a deep understanding of our data ecosystem and key business drivers.
* Deliver a first causal analysis or metric decomposition that directly informs a commercial decision.
* Prototype an initial agentic monitoring system for at least one core business metric.
In 12 Months
* A causal inference framework embedded into RevOps’ standard toolkit, shaping acquisition, retention, and revenue decisions.
* A suite of specialised AI agents running autonomously—monitoring key metrics and delivering proactive, plain‑language insight to stakeholders without manual intervention.
* Introduce and champion new methodologies (e.g. causal ML, uplift modelling, agentic workflows).
* Partner with stakeholders to embed ML products into key business workflows and decisions.
* Help shape the RevOps function’s research cadence and ways of working.
What We Offer
Competitive salary package, additional leave days, dedicated birthday leave, generous four‑week parental leave, international health and life insurance, wellness incentives, growth allowance, flexible working environment, and a supportive, multinational team.
EEO Statement
We are committed to fostering a workplace that values and celebrates diversity. We welcome individuals of all backgrounds and experiences, and we believe that a diverse and inclusive environment leads to innovation and success. We actively promote equal opportunities for all employees and strive to create a space where everyone's voices are heard and respected. Join us in our journey to build a truly inclusive workplace where every person can thrive and contribute to our collective success.
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