Strategy & Consulting - Global Network - H&PS -Health & Public Services – Consultant (Data & AI) job opportunity at Accenture Plc.

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Accenture Plc Strategy & Consulting - Global Network - H&PS -Health & Public Services – Consultant (Data & AI)
Experience: 5 years
Pattern: full-time
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Status:

Consulting

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degreeBachelor's (B.Sc.)
loacation San Jose, Costa Rica
loacation San Jose....Costa Rica

Job Title: GenAI Health AI Use Case Implementation Practice: Health & Public Service, Industry Consulting | Management Level: Analyst / Consultant (Level 11/9) | Location: Heredia / Costa Rica Explore an Exciting Career at Accenture Are you an outcome-oriented problem solver? Do you enjoy working on transformation strategies for global clients? Does working in an inclusive and collaborative environment spark your interest? Then, Accenture Strategy and Consulting is the right place for you to explore limitless possibilities. As a part of the Accenture Health Practice, our 4000+ practitioners across the globe, help our clients make a meaningful impact on patients’ lives through New Science, novel medical technologies and better collaboration. Together, let’s deliver more effective, affordable, personalized patient outcomes. In this practice, you’ll help drive our Healthcare clients’ strategy and business planning efforts, with the following initiatives Must Have Skills: Hands-on experience with AI/ML frameworks and tools such as TensorFlow, Prompt engineering, PyTorch, Scikit-learn, MLflow, Hugging Face, Azure ML, AWS SageMaker, AI/ML Model Development, GenAI Applications, GCP Vertex AI etc. Good-to-Have Skills: Familiarity with healthcare data standards (HL7, FHIR, ICD-10, SNOMED, CPT, etc.) and health frameworks Experience: Minimum 1-7 years of relevant experience in the health consulting domain Educational Qualification: B. Tech/B.E. (Tier 1 preferred) + MBA (Tier 1/2 preferred) Job Summary As a Health AI Implementation Consultant in Accenture’s Strategy & Consulting Global Network (S&C GN), you will work with leading healthcare and public service clients to design, develop, and deploy AI solutions that transform patient care, public health operations, payer efficiency, and provider services. Your role will span across AI/ML model development, data transformation, healthcare workflows, GenAI applications, and cloud enablement. You will design operating models, optimize processes, and enable AI-driven decision-making while supporting program management, business analysis, and value realization to help clients modernize healthcare delivery, improve outcomes, and accelerate digital transformation. Key Responsibilities: Understanding of healthcare ecosystems—payer, provider, and public health models—and exposure to global landscapes (US, Europe, Middle East, Asia-Pacific) is preferred. We welcome candidates who demonstrate strong problem-solving skills and an industry-driven mindset, with the ability to quickly adapt to health and public service contexts. Ability to design, test, and optimize prompts for LLMs that ensure contextual accuracy, reliability, and clinical/operational relevance. Hands-on ability to use lightweight Python code to interact with LLM APIs, build prompt libraries, and create repeatable workflows. Identify, assess, and solve complex business problems using domain expertise and GenAI techniques. Exposure to fine-tuning, evaluating, and applying LLMs (OpenAI, Anthropic, Cohere, LLaMA, Mistral, etc.) for healthcare/public service scenarios. Familiarity with healthcare data standards (e.g., FHIR, HL7, DICOM), electronic health records (EHRs), claims data, and public health datasets. Ability to frame prompts that incorporate structured and unstructured health data sources to deliver accurate outputs. Understanding of privacy, security, bias, and explainability requirements in AI-driven systems. Exceptional interpersonal and presentation skills to convey GenAI and prompt engineering value propositions to senior stakeholders. Support end-to-end delivery of AI/ML consulting engagements across healthcare domains such as clinical decision support, claims management, patient engagement, and public health analytics. Engage with client stakeholders (clinicians, payers, public health leaders) to conduct workshops and interviews for requirement gathering, capability maturity assessments, and AI adoption readiness. Conduct As-Is assessments of data flows and clinical/operational processes, and design To-Be AI-enabled workflows and operating models leveraging frameworks like Responsible AI (RAI) and data governance standards. Translate business needs into AI solution blueprints, process flows, user stories, and functional specifications for AI/ML implementations. Work closely with data engineers and technical teams to define AI/ML pipelines, identify automation opportunities, and develop AI transformation roadmaps. Analyze and optimize healthcare processes such as patient journey mapping, claims processing, service delivery, population health, and operational efficiency through AI models. Develop business cases, value driver trees, and performance KPIs aligned to AI transformation goals and value realization. Create high-quality client deliverables such as AI strategy documents, model design specifications, Responsible AI assessments, and actionable recommendations. Support business development initiatives, including RFP/RFI responses, go-to-market activities, proposal creation, and development of AI consulting assets and methodologies. Drive thought leadership by contributing to white papers, Points of View (POVs), and industry-focused research on AI in healthcare and public services. Ability to work in client-facing roles with some travel. Must Have Experience: Proven Prompt Engineering Experience: At least 2 hands-on projects involving the design of prompt libraries, reusable prompt frameworks, or healthcare-specific use cases. Education / Experience: MBA, MPH, or M.Tech from a Tier 1 institute is a plus. Alternative we value equivalent relevant industry experience in healthcare or public service consulting. GenAI & Digital Transformation Exposure: Experience in GenAI, data, and digital transformation initiatives with a focus on delivering measurable business value. Health Data & Interoperability: Familiarity with standards such as FHIR, HL7, and DICOM, with the ability to structure prompts around complex health data sources. Cloud AI Ecosystems: Practical understanding of Azure, AWS, or GCP AI services for deploying and scaling prompt workflows

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