Data Science Associate Manager

Job Role:

Data Science Associate Manager (Customer)
Team:
Song AI & Data – AI & Modelling Craft, UK&I

Location:

London / Manchester

Career Level:

Associate Manager (L8)
We Are Accenture Song accelerates growth and value for our clients through sustained customer relevance. Our capabilities span ideation to execution: growth, product and experience design; technology and experience platforms; creative, media and marketing strategy; and campaign, content and channel orchestration. With strong client relationships and deep industry expertise, we help our clients operate efficiently and sustainably through the unlimited potential of imagination, technology and intelligence.

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The Team Within Accenture Song sits AI & Data, the practice that builds the data-led intelligence behind the customer work. Song AI & Data helps organisations unlock value from data, analytics and AI by creating more relevant, personalised and effective customer experiences. Our expertise spans customer insight, data strategy and platforms, advanced analytics, performance optimisation, and AI (including generative AI and agentic AI) transformation.

You will join the Song AI & Data UK practice, within the AI & Modelling Craft: a community of data scientists, AI engineers, modellers and solution architects focused on applying AI, machine learning and advanced analytics to solve customer and growth challenges. Our teams work across the full lifecycle, from identifying opportunities and designing solutions through to building, deploying and operating AI products that deliver measurable business value.

The Role As a Data Science Associate Manager, you will lead the technical delivery of customer-focused analytics, data science and AI solutions. This is a hands-on role where you will own the technical quality of a workstream, make key analytical and modelling decisions, and write and review code alongside the team.

Your work could include analysing customer behaviour to identify growth opportunities; developing segmentation, propensity, churn or next-best-action models; building and evaluating generative AI and retrieval-augmented generation solutions; or developing agentic workflows that improve marketing, commerce or customer service processes.

You will move between hands-on delivery and workstream leadership, guiding data scientists and AI engineers while remaining close enough to the build to be accountable for its quality. You will structure ambiguous problems, select the right analytical approach and work with product, engineering, architecture and business teams to turn ideas and insights into solutions that can be deployed, adopted and scaled.

You will also work directly with clients, translating between technical, customer and commercial perspectives. Whether explaining a churn model to a marketing team, discussing AI risks with senior stakeholders or presenting experimental results, you will help clients understand how analytics and AI can create measurable customer and business value.

What You Will DoDesign and deliver customer analytics, data science, machine learning and generative AI solutions, from problem framing and data exploration through to production and measurable client value.

Make the technical decisions on your workstream, covering analytical approach, model and architecture selection, evaluation, guardrails, and cost and performance trade-offs.

Apply techniques including segmentation, experimentation, propensity modelling, churn prediction, customer lifetime value and next-best-action modelling to generate insight and improve customer decisions.

Write production-quality code and review the work of data scientists and AI engineers, including analysis, model design, code, prompts and data pipelines.

Establish robust approaches to data preparation, experimentation, validation and performance measurement, ensuring outputs are reliable, actionable and aligned to client objectives.

Work with engineering, architecture and product teams to take prototypes through to production, monitoring and scale using appropriate cloud and MLOps practices.

Lead the day-to-day technical delivery of a workstream, managing quality,…