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Accenture

Advises businesses and runs their technology

Data Architect

Applied Machine LearningConfirmed live in the last 24 hours
Full-timeChennai, Tamil Nadu, IndiaNo salary listed

About the Job

Requirements

  • A Bachelor's degree or equivalent.
  • At least 5 years of experience in Data Science.
  • At least 3 years of experience as a machine learning engineer or scientist deploying models in production at scale, including monitoring, alerting, automatic bug filing, and auditing.
  • At least 3 years of experience applying theoretical foundations of computer science, including computer system architecture, systems engineering, and programming.
  • At least 1 year of experience in distributed computing systems and architecture, which may include big data, high-performance computing, engineering simulations, scientific computing, grid and cloud computing, or distributed networks.
  • At least 1 year of experience building and deploying AI/ML-based software to a cloud environment.
  • Proficiency in Python and Python-based AI/ML frameworks, with familiarity with relevant libraries and frameworks such as TensorFlow and PyTorch.
  • Experience working with language-model APIs and optimizing their use for specific applications.
  • Experience with Python, C++, Java, R, and SQL.
  • Strong written and verbal communication skills, including the ability to communicate complex technical concepts to non-technical stakeholders.
  • Strong client-facing skills in a consulting environment.
  • Ability to collaborate with internal and client-side teams.
  • Fifteen years of full-time education.

Responsibilities

  • Define data requirements and structure for applications, and model and design application data structures, storage, and integration.
  • Formulate real-world problems into practical, efficient, and scalable AI and machine learning solutions.
  • Develop and implement machine learning algorithms, models, and computational systems.
  • Design and build scalable data pipelines to support model training and production with DevOps and MLOps.
  • Customize and apply deep learning and generative AI models for business use cases, accounting for data availability, system and infrastructure requirements, edge devices, and high-performance computing.
  • Research and develop AI and high-performance-computing algorithms, models, and simulations and their applications to complex business problems at client sites.
  • Work with large-scale datasets and apply data-preprocessing techniques to ensure high-quality training and production inputs.
  • Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge.
  • Justify the value of model approaches in business problems.
  • Collaborate with business and technical stakeholders, including users, use-case representatives, business owners, engineers, architects, and user-interface designers, to achieve end-to-end project goals and integrate solutions into production.
  • Collaborate with and manage the team to perform, and make team decisions.
  • Engage with multiple teams and contribute to key decisions.
  • Provide solutions to problems for the immediate team and across multiple teams.
  • Lead the development and implementation of data architecture standards and best practices.
  • Facilitate communication between technical teams and business units to ensure data requirements are met.
  • Mentor junior team members to support their professional growth and enhance team capabilities.
  • Design and model data architecture for efficient storage and seamless integration across systems, organizing data assets to support application functionality and scalability and aligning data strategies with business needs.

Desired Qualifications

  • Experience with Snowflake Data Warehouse, Amazon Web Services, and Databricks Unified Data Analytics Platform.
  • A Master's or PhD in a related field, such as computer science or engineering.
  • Familiarity with cloud-based data platforms and modern data-engineering tools.
  • Knowledge of data-modeling techniques and database-design principles.
  • Experience with data integration and data-storage solutions.
  • Ability to analyze complex data requirements and translate them into scalable data architectures.

About the Company

Accenture

Advises businesses and runs their technology

Accenture advises large businesses and public agencies on strategy, builds their technology systems and runs ongoing operations. Its teams connect business planning with implementation, covering areas such as cloud migration, cybersecurity and customer experience. Consultants work with clients to redesign processes, while engineers integrate software from technology partners and maintain the resulting systems for multinational organizations. Clients pay for project work or continuing services, including application support and business processes such as finance and customer service. Accenture was founded in 1989 and has its headquarters in Dublin, Ireland.

Company size
10,001+
Company stage
IPO
Headquarters
Dublin, Ireland
Founded
1989

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