Senior Data Scientist

We Are:

Accenture's Global Responsible AI team within the Global Data & AI Practice. AI is becoming more pervasive, more powerful and more accessible. With these new opportunities come increased risks. We work with leading organizations to ensure AI is designed, built and deployed in a manner that engenders trust and adheres to laws, regulations and ethical norms. Our Responsible AI strategy will enable us to embed responsibility into all of Accenture's data and AI activities. We're developing and deploying differentiated IP and Responsible AI solutions with our ecosystem partners. We'll be engaging regulators to help shape the policy agenda, conducting pioneering research with academia and offer training and resources to our clients through the Responsible AI Academy. The risks of AI are real and well- known . Let's help our clients turn those risks into opportunities.

You are:

We are seeking an experienced to design, develop, operationalize, and govern enterprise-scale artificial intelligence solutions.

You will bring broad expertise across advanced analytics, statistical modelling, machine learning, deep learning, natural language processing, computer vision, generative AI, and agentic AI, combined with a strong understanding of Responsible AI, AI governance, policy, standards, regulation, and risk management.

You will work with clients to translate emerging AI technologies, regulatory requirements, and Responsible AI principles into practical business outcomes. This includes helping organizations establish and implement AI principles, policies, governance structures, operating models, risk-management frameworks, controls, assurance mechanisms, and technology-enabled Responsible Senior Data Scientist AI capabilities.

The ideal candidate combines technical depth, business acumen, consulting experience, experimentation discipline, regulatory awareness, and strong stakeholder leadership. You will be comfortable moving between hands-on technical problem solving, executive-level advisory, client delivery, business development, and thought leadership.

You will work across industries and functional areas, helping clients take AI initiatives from strategy and discovery through experimentation, engineering, deployment, governance, monitoring, and continuous improvement. You will also contribute to Accenture's perspectives on emerging AI technologies, governance practices, standards, policy, and regulation.

The work:

• Partner with business, product, data, engineering, architecture, cybersecurity, legal, privacy, risk, compliance, and operations teams to identify, assess, and prioritize high-value AI opportunities.

• Translate complex business challenges into clearly defined analytics, machine learning, generative AI, agentic AI, and decision-science problem statements.

• Perform exploratory data analysis, statistical analysis, hypothesis testing, experimental design, feature engineering, predictive modelling, and optimization.

• Develop supervised and unsupervised machine learning solutions, including classification, regression, clustering, forecasting, recommendation, anomaly detection, optimization, and related techniques.

• Design and implement deep-learning solutions using neural networks, transformers, convolutional architectures, sequence models, representation-learning techniques, and multimodal approaches.

• Build natural language processing and computer vision solutions for document intelligence, information extraction, semantic search, knowledge discovery, image analysis, and multimodal understanding.

• Develop generative AI applications using large language models and foundation models, including prompt engineering, embeddings, vector search, retrieval-augmented generation, fine-tuning, model adaptation, guardrails, and evaluation.

• Design agentic AI solutions that combine reasoning, planning, memory, tools, workflows, human oversight, and single- or multi-agent orchestration to execute complex business processes.

• Evaluate commercial, open-source, and internally developed AI models and platforms based on performance, accuracy, robustness, cost, latency, scalability, security, privacy, explainability, maintainability, and operational fit.

• Design experimentation frameworks, evaluation methodologies, benchmarks, test datasets, acceptance criteria, and performance metrics for traditional, generative, and agentic AI systems.

• Collaborate with data engineers, software engineers, machine learning engineers, architects, cybersecurity specialists, and platform teams to operationalize scalable AI solutions using MLOps, GenAIOps, and LLMOps practices.

• Establish monitoring and observability for model performance, drift, bias, fairness, hallucination, toxicity, safety, latency, cost, resilience, and overall system reliability.

• Assess AI use cases and systems for risk across areas including fairness, transparency, explainability, privacy, security, robustness, human oversight, accountability, and regulatory compliance.

• Design and implement Responsible AI operating models, governance structures, policies, standards, controls, risk-assessment methodologies, assurance processes, and supporting technology capabilities.

• Advise clients on the implications of emerging AI legislation, regulation, standards, regulatory guidance, and industry practices.

• Maintain awareness of major developments in AI policy, regulation, technical standards, assurance, and governance and translate these developments into actionable guidance for clients.

• Support organizations in establishing AI inventories, classification and risk-tiering approaches, governance workflows, control libraries, documentation standards, testing frameworks, and ongoing monitoring.

• Act as a subject matter expert in Responsible AI within broader data, AI, cloud, digital, and enterprise-transformation programs.

• Shape and lead Responsible AI and AI-governance engagements, from initial assessment and strategy through design, implementation, operationalization, and continuous improvement.

• Engage with prospective clients to identify opportunities, shape solutions, develop proposals, and support sales conversations related to AI, Generative AI, Agentic AI, and Responsible AI.

• Lead client workstreams and multidisciplinary delivery teams, managing scope, outcomes, risks, dependencies, stakeholders, and delivery quality.

• Communicate analytical findings, AI-system behavior, limitations, risks, trade-offs, and business implications to both technical and non-technical stakeholders.

• Provide guidance to senior Accenture leaders and client executives on AI strategy, adoption, governance, risk, regulation, and emerging technology.

• Engage with relevant industry, policy, standards, regulatory, academic, and ecosystem stakeholders where appropriate.

• Develop and present Accenture perspectives, methodologies, accelerators, research, and thought leadership on AI and Responsible AI.

• Mentor data scientists and other practitioners and contribute to reusable frameworks, standards, assets, accelerators, and communities of practice.

• Support clients with AI strategy, capability development, technology selection, organizational change, workforce adoption, and responsible scaling of AI.

Travel may be required for this role. The amount of travel will vary from 0 to 100% depending on business need and client requirements.