Join our dynamic Data & AI practice, a global network dedicated to helping clients achieve high performance through data-driven insights. We empower organizations to transform data into actionable strategies, from advanced analytics to predictive modeling. As part of our team, you'll contribute to developing innovative AI and data solutions for SaaS and PaaS clients, collaborating with international teams to drive growth and deliver exceptional results.

Accenture invests continuously in your professional development, offering opportunities to work with leading experts and expand your technical expertise. You will gain a deep understanding of analytical decision-making and project execution within business performance improvement initiatives, shaping the future of AI and data application.

Develop and test sophisticated AI algorithms and techniques, precisely tailored to solve complex business challenges. Expertly manage large databases, performing exploratory data analysis to uncover critical insights for stakeholders. Investigate historical data meticulously, posing insightful questions to pinpoint root causes of issues. Employ a structured problem-solving methodology, exploring all avenues and asking pertinent questions to understand core problems.

Collaborate effectively with internal teams and external consultants to achieve project objectives. Build and maintain robust data pipelines for streamlined information flow and enhanced efficiency. Adapt readily to evolving project requirements and embrace continuous learning to stay ahead of industry trends and advancements.

We are seeking candidates with a Bachelor's or Master's degree in computer science, engineering, data science, or a related discipline. Essential experience includes working with large Software or Platform organizations and at least two years of proven experience in AI projects, delivering successful outcomes.

Hands-on expertise with Generative AI frameworks like Azure OpenAI and Vertex AI is crucial, alongside a strong understanding 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, and time series analysis, is required.

Demonstrated ability to work with substantial datasets and present findings clearly to key stakeholders is vital. Expertise in data management using SQL databases and proficiency in statistical packages like R, Python, Java, SQL, and Spark are expected. Experience in training and fine-tuning large language models, coupled with familiarity with cloud platforms (AWS, Azure, GCP) for model deployment, is highly valued.

Exceptional analytical and problem-solving skills, driven by a data-centric mindset, are paramount. Proficiency in standard office software, including Excel, MS Word, and PowerPoint, is also necessary.