Experienced customer insight analyst to deliver impact across loyalty partners.
Compensation
You'll receive an annual holiday allowance and you can buy additional holiday. We also offer other benefits that will help your money go further such as season ticket loans, cycle to work scheme, health cash plans, pay advance (where you can access some of your pay before pay day) as well access to a great range of discounts from hundreds of other retailers. And if you ever need it there is also an employee assistance programme. Moments that matter are as important to us as they are to you which is why we give up to 26 weeks pay for maternity or adoption leave and up to 4 weeks pay for paternity leave.
Responsibilities
Collaborate with internal teams and clients to define analytical approach
Own complex analytical projects end-to-end
Generate actionable insights
Enhance processes and experiment with new data sources
The single, hands-on owner of analytics for client accounts, taking requests from the first message to a readout without supervision, providing insights, outcomes reporting, and strategic perspective.
Responsibilities
Own the analytics workstream on client accounts, running request intake and prioritisation within agreed hours and flagging project-sized requests
Act as the client’s go-to contact for data questions, testing question framing before analysis
Write production-quality SQL in the client’s warehouse (Snowflake, Databricks or similar) and develop transformation logic
Trace data lineage, fix gaps in existing reports, SQL and data events, and reconcile metrics across systems (Amplitude, GA4)
Run cohort, behavioural and decomposition analysis on transaction and loyalty data (ATV, revenue, frequency, retention, LTV)
Global GTM Practice Architect for Agentic Data Cloud within Google Cloud, responsible for owning global strategy and business goals, driving GTM motion, and partnering with cross‑functional teams.
Partner with Account Executives through the full sales cycle: discovery, solutioning, demos, proof of concepts, RFP responses, and handoff to the implementation team
Run structured discovery conversations that uncover the business value a prospect has not yet articulated for themselves, in their data, workflows, or current tech stack, and build that into a clear value case
Design and deliver product demonstrations that walk a prospect from that value case straight into the platform mechanics that deliver it, showing exactly how MoEngage's core capabilities and AI decisioning engine get them there
Lead technical validations and proof of concepts that prove out the value case with the prospect's own data, working with engineering and solutions architecture where needed
Write clear, accurate responses to RFPs and RFIs, including technical architecture and integration questions
The Manager, Data Science leads the vision and technical execution of data science and marketing science across Marketing and Product. This is a hands-on technical role spearheading marketing measurement strategy, predictive growth models, and mentoring a team.
Compensation
Base salary range: $140,000 - $180,000
Responsibilities
Define and drive the data science and marketing science vision for Marketing and Product, establishing high technical standards.
Own the end-to-end marketing measurement framework, unifying media mix modeling (MMM), incrementality/geo testing, and multi-touch attribution.
Architect, build, and deploy high-impact predictive models—including client lifetime value (LTV), cross-sell/upsell propensity, and churn/retention.
Hold all data science products to strict production criteria: ensuring business value is sized upfront and models are validated.
Maintain an active hands-on engineering presence by writing, debugging, and reviewing production Python, SQL, and dbt models.
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