Join Accenture's Global Network - Data & AI practice, where we empower clients to achieve high performance through data-driven insights. Our forward-thinking consultants deliver analytically informed solutions to improve outcomes and strengthen customer relationships. This role is integral to our mission of developing and deploying cutting-edge AI and data solutions for SaaS and PaaS clients.

Accenture is committed to your continuous learning and growth. You will collaborate with experts in SaaS & PaaS, expand your tech stack, and pursue relevant certifications. Within the Data & AI practice, you will gain a deep understanding of sound analytical decision-making and its impact on overall project success.

Develop and test AI algorithms and techniques tailored for complex business challenges. Proficiently manage large databases, conducting exploratory data analysis to extract valuable insights. Investigate historical data and ask probing questions to identify root causes of problems. Employ systematic problem-solving approaches to unravel core issues. Collaborate effectively with internal teams and external consultants to meet project objectives.

Develop and manage efficient data pipelines. Demonstrate adaptability to evolving project requirements. Proactively seek continuous learning opportunities to stay abreast of industry trends and advancements in AI and data science.

We are seeking candidates with a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related field, complemented by 2+ years of proven experience in AI projects. Significant hands-on exposure to Generative AI frameworks like Azure Open AI and Vertex AI is essential, alongside a strong grasp of AI technologies such as embedding, prompt engineering, NLP, and computer vision.

Proficiency in building and deploying statistical and machine learning models, including segmentation, predictive modeling, hypothesis testing, multivariate analysis, time series techniques, and optimization, is required. The ability to work with large datasets, present findings to stakeholders, and manage data using databases like SQL is crucial. Familiarity with statistical packages such as R, Python, Java, SQL, and Spark is expected. Experience in training large language models, fine-tuning them for specific applications, and deploying them on cloud platforms (AWS, Azure, GCP) is highly advantageous. Excellent analytical and problem-solving skills with a data-driven mindset, along with proficiency in Excel, MS Word, and PowerPoint, are also key.