Data Science Associate Manager

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.

Design 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 included 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, risks and dependencies while coaching and developing team members. Communicate analytical findings, technical choices, limitations and trade-offs to technical teams and senior business stakeholders, connecting the work to customer and commercial value. Contribute to proposals, solution approaches, estimates, reusable assets and best practices for customer-focused data and AI opportunities.

Our Total Rewards consist of a competitive basic salary, annual performance bonus, opportunities to acquire equity and a wide range of health and wellbeing benefits.

• 25 days of leave to spend each year plus 3 extra volunteering days per year for charitable work of choice.
• Family-friendly and flexible work policies.
• Attractive pension plan with financial wellbeing support and resources.
• Private healthcare insurance plan and Mental Wellbeing support.
• Employee Assistance Programme, Career Development and Counselling.
• A range of generous Parental Leave offerings.

• Hands-on data science and AI delivery in the customer domain.
• Experience building and delivering machine learning, generative AI or LLM-based solutions in real client or product environments, applied to customer growth, personalisation, marketing, commerce, sales or service.
• You can explain how a solution works, the decisions you made and the value it created.
• Strong Python capability.
• You can write production-quality Python and review and improve the code, analytical methods, model designs, prompts and pipelines produced by others.
• Data science and analytics fundamentals.
• Strong understanding of exploratory analysis, statistical methods, experimentation and machine learning, including experience developing, evaluating and deploying…