About the Role

Accenture Song is looking for a Data Science Associate Manager to join our Data & AI practice. In this role, you'll partner directly with clients to design and deliver data science and AI-driven solutions that solve real business problems — from marketing optimization to next-generation agentic and generative AI applications. You'll act as both a hands-on technical contributor and a trusted advisor, translating complex analytical work into clear business value for senior stakeholders.

What You'll Do

1. Design, build, and deploy data science and machine learning solutions for customer and marketing use cases
2. Serve as a trusted advisor to client stakeholders, building strong working relationships and guiding technical decision-making
3. Apply emerging AI capabilities — including agentic systems, RAG, and knowledge graphs — to practical business problems
4. Translate complex technical findings into clear narratives and recommendations for both technical and non-technical audiences
5. Collaborate with cross-functional teams across data engineering, strategy, and creative to deliver end-to-end solutions

Minimum Qualifications

1. 7+ years of experience in data science, machine learning, and business analytics
2. Experience in a client-facing or consulting environment, with a track record of building trusted relationships with stakeholders
3. Strong programming skills, with proficiency in Python required
4. Working knowledge of one or more of the following:
5. Agentic AI systems and architecture
6. Knowledge graphs (GraphRAG)
7. Retrieval-Augmented Generation (RAG)
8. Hands-on experience with at least one major cloud platform (AWS, GCP, or Azure)
9. Excellent verbal and written communication skills, with the ability to present data and insights clearly to varied audiences
10. Strong analytical thinking paired with creative problem-solving ability

Preferred Qualifications

1. Experience working with GenAI / large language models (LLMs), with genuine enthusiasm for staying current on advances in generative AI and applied machine learning
2. Broad understanding of data management practices, including reference data management, data quality improvement, metadata management, data marketplaces, and data governance
3. Proficiency with marketing and web/app analytics tools such as Adobe Analytics, Adobe Target, Adobe CJA, Google Analytics, NetInsight, AppsFlyer, WebTrends, Optimizely, SEMrush, or Firebase
4. Experience with tag management platforms (GTM, Adobe Launch, Tealium), ad conversion pixels, or data management platforms (DMPs)