Healthcare Payer AI Decision Science Consultant

Accenture•Milwaukee, NY

8d•Hybrid

About The Position

Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth, and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 774,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, AI and data with unmatched industry experience, functional expertise, and global delivery capability. We are uniquely able to deliver tangible outcomes because of our broad range of services, solutions and assets across Consulting, Strategy, Technology, Operations, Industry X and Song. These capabilities, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners, and communities. Visit us at accenture.com. We work with C-suite executives, leaders and boards of the world’s leading organizations, helping them reinvent every part of their enterprise to drive greater growth, enhance competitiveness, implement operational improvements, reduce cost, deliver sustainable 360° stakeholder value, and set a new performance frontier for themselves and the industry in which they operate. Our deep industry and functional expertise is supported by proprietary assets and solutions that help organizations transform faster and become more resilient. Our Decision Science practitioners use Industry & Functional domain expertise along with agentic AI knowledge to design, develop and reinvent processes with AI to drive efficiency and growth. You will be responsible for leveraging advanced analytics, machine learning, and AI technologies to create decision-making systems. This role requires a blend of strong analytical mindset, technical expertise, and the ability to communicate complex findings for both technical and non-technical stakeholders to deliver innovative solutions aligned with Accenture’s commitment to driving 360° value for clients. This is an industry-specific role focused on the healthcare payer domain—designing AI solutions that fit payer operations, data, and the regulatory environment, and that create real leverage across the member and provider lifecycle.

Requirements

Bachelor’s Degree, preferably in Data Science, Computer Science, Statistics, or a related field.
3+ years of experience in Data Science, Machine Learning, AI, or Advanced Analytics.
Understanding of core payer functions and operations: prior authorization, claims / utilization management, member engagement, care management, and risk adjustment.
Comfortable with payer data—claims, eligibility, and benefits—and the regulatory environment (e.g., HIPAA, CMS).
Hands-on experience using Claude or an equivalent frontier AI tool to do the work.

Nice To Haves

3+ years of experience building decision-based frameworks and models to drive insights.
3+ years of high value consulting experience or equivalent internal consulting experience.
3+ years of experience leading workstreams and meeting deadlines.
3+ years of large-scale delivery experience with minimal help.
Proven track record of developing and implementing data-driven solutions.
Proficiency in programming languages such as Python, R, or SQL.
Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
Strong analytical and problem-solving skills.
Experience with AI Native and cloud platforms (e.g., Open AI, Anthropic, AWS, Azure, Google Cloud).
Knowledge of big data technologies (e.g., Hadoop, Spark).
Knowledge of agent-based modeling, reinforcement learning, and autonomous systems is highly desirable.
Familiarity with data visualization tools (e.g., Tableau, Power BI).
Strong program management and communication skills, both verbal and written.
Fluent in English (both spoken and written).
You have experience bringing innovative ideas to projects.
Master’s degree in Data Science, Computer Science, Statistics, or a related field.
Experience delivering AI or technology programs inside payer organizations.

Responsibilities

Assist in the delivery of Data Science, Artificial Intelligence, Analytics initiatives / program for healthcare payer clients
Collaborate with onshore and offshore teams to execute projects.
Work forward-deployed with payer clients, co-creating solutions using our platforms and AI tooling to move quickly from idea to working solution.
Understand and be able to bridge between business and technical domains (for both internal and external purpose)
Engage with business and analytics stakeholders to understand their needs and build relationships.
Support the sales process by contributing to sales solutioning for DS & ML related opportunities.
Develop and customize DS / ML / AI / Analytics models and solutions for specific business problems within an industry or function.
Help scope payer-focused AI programs and target high-value payer functions such as prior authorization, claims and utilization management, member engagement, care management, and risk adjustment.
Collaborate across Accenture’s network and partner with strategy, consulting, and tech teams in the sales and delivery processes.
Identify AI use cases in an industry and/or function by understanding an organization’s goals and areas of need, developing the business case, determining ROI, and creating the transformation roadmap.
Contribute to the technical architecture of AI programs in payer environments, designing for payer data and compliance constraints, and help reimagine the future way of working for payer operations rather than simply automating today’s processes.
Advise organization on adoption of responsible AI solutions and governance by training users on new processes, maintaining solutions, tracking results, and communicating the realized value.