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About the role
This role is in Accenture Research Global Data Science Team, and it will be fully dedicated to support research projects in terms of data provisioning and development of research solutions.
We are looking for curious candidates that will combine data engineering skills, creativity, and analytical capabilities to accelerate Accenture’s data-driven business research and insight discovery.
We offer a career aligned to our priority of creating innovation and impact, managing complex data driven research projects, with multinational and multidisciplinary teams. We provide opportunities for coaching, supervision and mentoring, as well as responsibilities to manage dedicated research budgets and relationships with external partners.
Key Responsibilities include:
• Support global and local research projects on themes aligned to our Accenture Research global priorities and efforts.
• Design, develop and maintain data solutions in cloud environment.
• Promote and implement best practices and modern approaches for big data processing and management.
What we offer:
• We have access to 100+ business data sources through our research data lake. We are constantly expanding our universe of data from commercial and open sources and partnering with premium data providers to improve quality of inputs into our models.
• We provide several unique training opportunities to continue your growth, including both internal trainings, on the job, personal exploration time to work on novel methodologies without the constraints of a projects and with leading universities.
Experience and skills:
• “Hard” skills:
• Experience in developing GenAI tools and building the necessary architecture to support development.
• Proven knowledge of GenAI frameworks like Langchain, LLamaindex, etc…
• Skills in building, maintaining and querying VectorDB, Milvus is preferred.
• Experience with both closed LLMs (Azure OpenAI, Claude) and open source LLMs (LLAMA, Falcon…)
• Practice in designing and development of data pipelines and processes orchestration.
• Experience in designing data architecture and governance, data warehousing, data quality management, master data management.
• Excellent knowledge of Python language, particularly in processing of structured and unstructured data
• Proficiency in SQL for processing large datasets
• Skills in working on Linux/Unix operational system.
• Ability to work with CI/CD tools.
• Knowledge of GCP data services: Cloud Composer, Big Query and Dataflow
• Practice in development of application integration solution is an advantage.
• “Soft” skills:
• Strong analytical skills and a proven ability to deliver high quality data products.
• Understanding of business requirements and how to convert them into data processing solutions.
• Ability to handle multiple projects simultaneously and prioritize appropriately and effectively.
• Problem solver approach to work and entrepreneurial attitude
• Strong professional qualities: client focus, decisivenes