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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Manager - Data Science (Martech/CRM) - **Company:** VML group - **Location:** Greater London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Cluster Analysis, Data Governance, Extract Transform Load (ETL), Data Systems, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, NoSQL, Recommender Systems, Salesforce.Com, Adobe, Virtual Agents - **Published:** September 10, 2026 - **Apply:** https://www.collegerecruiter.com/job/2840587014-senior-manager-data-science-martechcrm ## About the Role * 5-8 years of hands-on data science experience combining technical depth with client advisory. * Strong expertise in statistical analysis, experimentation, ML techniques (regression, classification, clustering, hypothesis testing, next best action modelling). * Proficiency in Python and advanced SQL. * Solid grasp of adjacent domains: data modelling, ETL/ELT strategy, no-SQL databases, pipeline design-enough to collaborate credibly with engineers and architects. * Domain knowledge in CRM and marketing technology: campaign metrics, measurement frameworks, and experience with platforms such as Adobe, Salesforce, or Braze. * Cloud platform experience (GCP, AWS, or Azure). Advisory & Business * Consulting craft: run client conversations end-to-end - scoping problems, shaping proposals, writing SOWs, contributing to RFPs, and defending recommendations under challenge. Comfortable moving between boardroom narrative and technical detail in the same meeting. Prior consulting or agency experience expected. * Commercial & advisory instinct: track record of identifying data-driven opportunities, building maturity roadmaps, and translating data science into business outcomes. Sound judgement on effort, ROI, and prioritisation by impact. People Management * Demonstrated experience managing a team: mentoring, performance reviews, hiring, and day-to-day support. Formal management experience is essential. * Coaching-oriented leadership style. You grow people through trust, feedback, and investment-not top-down direction. * Comfort scaling a team that's still taking shape: anticipating needs, defining roles, onboarding effectively. * Emotional intelligence, empathy, and conflict resolution skills. Excellent communication skills in English., * Agency or consultancy experience in fast-paced, multi-client environments. * CRM certifications (e.g., Adobe CJA, RTCDP). * Familiarity with data governance and privacy (GDPR, CCPA). * Experience with out-of-the-box vendor intelligent services. * Exposure to agentic AI or AI-driven automation use cases. * Management or leadership certifications. ## Description Client demand is growing. And you'll have real autonomy to shape what this practice becomes: the product offering, the ways of working, and how data science becomes an accelerator that elevates the work of activation, engineering, and insights teams around you. * Lead & Grow the Team: Manage a team of data scientists end-to-end; hiring, onboarding, personal development, performance conversations, and day-to-day support. Coach team members technically and professionally. Identify skill gaps, plan for future needs, and scale the team as the practice grows. Foster a culture of knowledge sharing, curiosity, and quality. * Build, Not Just Oversee: Personally contribute to high-complexity initiatives; designing and shipping ML models, training and inference pipelines, and experimentation frameworks. Bring deep, hands-on expertise in marketing-relevant techniques: uplift modelling, propensity scoring, attribution, next best action modelling, segmentation, causal inference, and recommender systems. Set the technical bar through code and craft, not just review. * Advise Clients Strategically: Partner with account and strategy teams on scoping, proposals, and commercial conversations: you're a credible voice in the room when clients are deciding where to invest. Act as a trusted data advisor. Proactively identify gaps and untapped opportunities in clients' data and marketing ecosystems. Translate complex findings into business recommendations. Anticipate business needs and challenges; build lasting client relationships as the go-to person for data science matters. * Deliver End-to-End with Quality: Lead complex data science initiatives from hypothesis and experimentation through model development, validation, and activation. Collaborate closely with Data Engineers and Architects so solutions are grounded in solid infrastructure. Own quality across all team deliverables, with discipline in statistical methods, reproducibility, and insight generation. * Lead the team into Agentic AI: Champion agentic AI as both a way of working and a delivery capability. Coach data scientists to adopt AI-native engineering practices (agentic coding, AI-assisted development, prompt and context engineering) and lead the design of agentic solutions for clients: from internal accelerators to production-grade agents embedded in marketing workflows. We expect you have shipped or prototyped agentic solutions and have a clear point of view on where they create real value. * Apply CRM & Marketing Domain Expertise: Contextualize data science within clients' CRM, campaign, and personalization strategies. Leverage hands-on experience with platforms like Adobe AEP, Salesforce Data Cloud, or Braze to extend marketing measurement and influence communications from a data perspective. * Shape the Practice: Establish guidelines, ways of working, and reusable accelerators. Maintain a backlog of data science use cases. Contribute to road-mapping, maturity frameworks, and the data science product catalogue alongside the Global Data Practice Lead. ## Related Videos - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [3x Performance: A Humbling Journey](https://www.wearedevelopers.com/videos/100165-3x-performance-a-humbling-journey) - [Leveraging Real time data in FSIs](https://www.wearedevelopers.com/videos/806-leveraging-real-time-data-in-fsis) - [AI Vector Search at Scale - Ewa Szyszka - Ewa Szyszka](https://www.wearedevelopers.com/videos/2161-ai-vector-search-at-scale-ewa-szyszka-ewa-szyszka) - [The Data Mesh as the end of the Datalake as we know it](https://www.wearedevelopers.com/videos/156-the-data-mesh-as-the-end-of-the-datalake-as-we-know-it) ## Related Articles - [Coffee with Developers - Maria Apazoglou - Making AI understandable for all in production](https://www.wearedevelopers.com/magazine/475-coffee-with-developers-maria-apazoglou-making-ai-understandable-for-all-in-production) - [Should Tech Managers Be Developers First? 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