Join Accenture's Global Network - Data & AI practice to help clients achieve high performance through data-driven insights. This role focuses on developing advanced analytics capabilities and providing strategically informed insights at scale. You will be part of a dynamic team dedicated to creating innovative Data & AI solutions for SaaS and PaaS clients, collaborating with global experts to enhance business outcomes. Accenture is committed to continuous investment in your learning and growth, supporting your technical development and certifications.

Develop and rigorously test AI algorithms and techniques tailored to complex business challenges. Proficiently manage large datasets, performing exploratory data analysis to uncover critical insights for stakeholders. Investigate and meticulously analyze historical information to identify root causes of issues, employing a systematic problem-solving approach. Collaborate effectively with internal teams and external consultants to achieve project goals. Build and maintain robust data pipelines for efficient information flow. Demonstrate flexibility and adaptability in responding to evolving project requirements. Actively pursue continuous learning to stay abreast of industry trends and advancements.

We are seeking individuals with a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field. Experience working within large Software or Platform organizations is essential. Candidates should possess a minimum of 2 years of proven experience in AI projects, delivering successful outcomes. Hands-on exposure to Generative AI frameworks like Azure OpenAI and Vertex AI, along with strong knowledge of AI technologies including Embedding, prompt engineering, NLP, and computer vision, is required. Experience building and deploying statistical and machine learning models, covering segmentation, predictive modeling, hypothesis testing, multivariate statistical analysis, time series, and optimization is necessary. Ability to manage and present findings from large datasets using databases like SQL is a must. Proficiency in statistical packages such as R, Python, Java, SQL, and Spark is essential. Familiarity with training and fine-tuning large language models for specific applications, and experience with cloud platforms like AWS, Azure, or Google Cloud for model deployment and scaling, are highly valued. Excellent analytical and problem-solving skills with a data-driven mindset, alongside proficiency in Excel, MS Word, and PowerPoint, are expected.