Lead Data Analyst (Loyalty)

• Own the measurement framework end to end: what is measured, how each metric is defined, how a result is proved, and what the organisation is entitled to claim from it
• Design and own the control-group, holdout and incrementality approach that separates genuine behaviour change from background activity
• Set the canonical metric definitions every party works to, and hold them stable as the single source of truth
• Own the analytics and insight roadmap: what gets built, in what order, and what is deliberately not built
• Set the analytical standards, tooling and ways of working used across the Loyalty practice, and represent the discipline in practice-level capability planning
• Be accountable for the evidence the programme uses to prove its value, and for that evidence surviving challenge up to client board level
• Be accountable for delivering the benefit-realisation position at each programme gate, on the gate date, to the standard the clients assurance process requires
• Be accountable for the commercial value attributed to the measurement function, and report honestly where performance falls short of forecast
• Prioritise the analytics backlog against programme milestones, the release train and the governance calendar, and defend those choices when challenged
• Sequence measurement design so instrumentation is specified ahead of build rather than retrofitted after launch
• Balance long-run capability building against immediate demand, and make the trade-off explicit rather than absorbing it
• Judge when a result is robust enough to act on and when it is not, and say so
• Identify where a measurement approach carries risk, such as contaminated control groups, missing instrumentation or unresolved consent constraints, and escalate with a recommended course of action
• Assess the analytical consequences of design, data and platform decisions before they are taken, and own the analytical entries on the programme risk register
• Represent the measurement position at the programmes design and technical authorities, bringing evidence and a recommendation rather than a set of options
• Work across design, technology, marketing, legal and the clients own data teams to secure the instrumentation and data access that analysis depends on
• Translate findings into decisions for people who are not data specialists, at every level up to executive, and build the case for change where the evidence points somewhere the programme did not expect to go
• Quantify the commercial value of loyalty and CRM activity, identify where value is being lost, and convert model outputs into recommendations with a named owner and a sizing
• Own forecasting for member value, retention and programme performance, and the variance analysis behind it
• Own predictive modelling and segmentation - propensity, churn, lifetime value, next-best-action - and the derived variables that drive personalisation
• Own the test-and-learn framework and the optimisation roadmap, and lead improvement initiatives in how loyalty is measured, not only in how this programme is measured
• Act as the senior specialist for the discipline: set the method standard, assure the quality of analytical output produced across the programme, and develop less experienced colleagues

Technologies:

• CRM
• Excel
• HubSpot
• LESS
• Marketing
• Power BI
• Python
• SQL
• Salesforce
• Tableau
• Support

More:

Collinson is the global leader in travel experiences and customer engagement, building loyalty 500 million times a day across 140 countries for ambitious brands including major financial institutions, airlines, transport operators and retailers. Our loyalty practice sits at the intersection of behavioural strategy, data science and programme design, with a focus on incrementality as the true measure of a programmes worth. This senior specialist role owns the measurement and insight function for a flagship loyalty programme, working within a collaborative governance structure and partnering with the client, a global platform vendor, design teams and multiple delivery partners. We offer the opportunity to work on strategic and visible client programmes in a fast-paced environment, with a purpose-driven, high-performing culture guided by our values: Take Action, Do the right thing, One team and Be insight led. We are an equal opportunity employer and welcome differences in all their forms.

• Minimum 5 years experience as a data analyst in complex, multi-channel customer environments, including at least 3 years owning an analytical function, service or workstream rather than a task queue
• Demonstrable end-to-end ownership of a measurement or insight capability: we set the approach, defended it, and were accountable for what it produced
• Experience designing incrementality measurement, including control groups, holdouts and test design, and defending the results to stakeholders with a commercial interest in a different answer
• Experience acting as the senior analytical authority in a multi-party delivery environment: setting method standards others work to, assuring output produced by partner and client-side teams, and developing less experienced colleagues
• Track record of influencing senior stakeholders with evidence, including where that evidence was unwelcome, and of prioritising an analytics backlog against competing demands
• Comfort operating within a formal governance structure: design authorities, change control and documented decisions
• Strong SQL and Excel, Python or R for statistical work, BI tools such as Power BI or Tableau, and marketing automation or customer data platforms such as Salesforce, Braze, HubSpot or Klaviyo
• Personally accountable for predictive models and customer segmentations that have run in production
• Deep command of retention, lifetime-value and incrementality metrics in a CRM, loyalty or lifecycle-marketing context, with the judgement to know when a result looks wrong
• Loyalty, CRM or lifecycle marketing delivered at scale
• Experience in a regulated or public-facing environment where data use is externally scrutinised
• Exposure to consent frameworks and the constraints they place on measurement design
• Sets a standard and holds it, including when holding it is inconvenient
• Makes and defends decisions on incomplete information, and states the confidence attached to them
• Comfortable being the person who says the number is not good enough yet
• A clear communicator who leads with the decision rather than the method
• Builds standards other teams choose to adopt, and raises the capability of the analysts around them