Data Science Research Manager - Accenture Research

About the role

We are looking for a manager-level data scientist who brings a rare combination of very strong business acumen and technical fluency. You will support high-impact client engagements across industries by designing and deploying machine learning models, genAI pipelines, and agentic AI workflows. You will be a core contributor to the team’s portfolio of reusable, scalable analytical assets — including synthetic persona systems and intelligent agent frameworks — built on a GCP-first technology stack.

Responsibilities

• Translate complex business problems into well-scoped, researchable analytical questions with clearly defined outputs and success metrics
• Collaborate with research leads, economists, and client-facing teams to embed AI-native tools into project delivery
• Design, build, and deliver ML and genAI-powered analytical methodologies to support client engagements across multiple industries
• Develop and iterate synthetic persona generation pipelines, including large-scale digital executive personas and behavioral simulation models
• Implement agentic AI workflows using frameworks such as Google ADK, A2A, and MCP protocols on GCP
• Design and maintain real-time intelligence dashboards and AI-as-a-service analytical assets
• Coach and mentor junior data scientists, fostering a culture of technical rigor and business relevance

Qualifications

• Minimum of 5 years delivering analytical outputs in client-facing or commercial settings, with demonstrated ability to translate technical findings for executive audiences
• Minimum of 5 years applying machine learning methods, including simulations, supervised/unsupervised models, NLP, and time series
• Minimum of 2 years of experience with generative AI — including LLM prompting strategies, retrieval-augmented generation (RAG), and multi-modal models
• Minimum of 2 years of hands-on experience designing and building agentic AI architectures, including tool-use patterns, planning loops, and multi-agent orchestration
• Bachelor’s degree in Data Analytics, Data Science, Strategy, Economics, or a related field with minimum 5 years of work experience. Master’s degree with minimum 5 years of work experience. PhD is a plus

Requirements

• Minimum of 5 years applying machine learning methods, including simulations, supervised/unsupervised models, NLP, and time series
• Minimum of 2 years of experience with generative AI — including LLM prompting strategies, retrieval-augmented generation (RAG), and multi-modal models
• Minimum of 2 years of hands-on experience designing and building agentic AI architectures, including tool-use patterns, planning loops, and multi-agent orchestration
• Bachelor’s degree in Data Analytics, Data Science, Strategy, Economics, or a related field with minimum 5 years of work experience. Master’s degree with minimum 5 years of work experience. PhD is a plus
• Python (advanced): modeling, data wrangling, pipeline development, and API integration
• Machine learning: supervised and unsupervised methods, ensemble models, time series, NLP, and text analytics
• Generative AI: LLM prompting, fine-tuning, retrieval-augmented generation (RAG), and multi-modal models
• Agentic AI: experience building agent architectures including tool use, planning loops, and multi-agent orchestration
• Synthetic data generation: methods such as SDV, Gaussian Copula Synthesizer, IPF calibration, or equivalent
• Google Cloud Platform (GCP) — critical requirement: Cloud Run, BigQuery, Vertex AI, Secret Manager, and GCP deployment architecture

Skills

• Strong business acumen: ability to contextualize analytical findings within industry dynamics and C-suite decision-making
• Excellent communication skills — written, verbal, and visual — for presenting to executive and non-technical audiences
• Strategic problem-solving mindset: comfortable moving from ambiguous business context to a structured analytical approach
• Strong project and stakeholder management capabilities in fast-paced, global environments
• Enthusiasm for cross-functional, multicultural teamwork with a bias toward building durable, reusable infrastructure

Benefits

Compensation at Accenture varies depending on a wide array of factors, which may include but are not limited to the specific office location, role, skill set, and level of experience. As required by local law, Accenture provides a reasonable range of compensation for roles that may be hired as set forth below.

Pay

Annual Salary Range: $94,400 to $266,300

Schedule

The work location for this role will include a mix of working remotely and working onsite. With all our roles, there is some in-person time for collaboration, learning and building relationships with clients, peers, leaders and communities. As an employer, we will be as flexible as possible to support your specific work/life needs.