Employment type in the employer’s posting: Full timeFrom the employer’s posting
Define data requirements and structure for applications
Model and design application data structure, storage and integration
Lead development of data architecture standards and best practices
Facilitate communication between technical teams and stakeholders
Mentor junior team members
Define the data requirements and structure for the application.
Model and design the application data structure, storage and integration.
Lead the development and implementation of data architecture standards and best practices.
Facilitate communication between technical teams and stakeholders to ensure data requirements are met.
Mentor junior team members to support their professional growth and enhance team capabilities.
The candidate should have minimum 12 years of experience in Data Science.
Must To Have Skills: Proficiency in Data Science.
Strong knowledge of data modeling techniques and database design principles.
Experience in designing scalable data storage solutions and data integration strategies.
A 15 years full time education is required.
Experience with Snowflake Data Warehouse, Amazon Web Services (AWS).
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale.
In the employer’s words · Read in context
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Day 25
Similar jobs usually come down between day 8 and day 76.
Well past Accenture’s usual: its jobs come down by about day 1.
From 5,460 similar postings that came down, and 2,606 of Accenture’s. Coming down is not always a hire.
250 open jobs
Open jobs by the week we first saw them, last 12 weeks.
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As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle — assessing client needs and data, selecting and customizing models (including Deep Learning, Generative AI, and Large Language Models), designing scalable data and MLOps/LLMOps pipelines for training and production, and ensuring quality, value, and reliability of deployed systems. 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 & MLOps Customize and apply Deep Learning and Gen AI models for various use cases based on the business needs, data availability, system and infrastructure requirements - including edge device and HPC Engage in research and development of new AI and high-performance compute algorithms, models, and simulations along with their applications to solve complex business problems at client sites Work with large-scale datasets and utilize data preprocessing techniques to ensure high-quality input for training and production Implement and maintain efficient data storage and retrieval mechanisms for models and knowledge using appropriate tools Justify the value of model approaches in business problems Collaborate with teams from both business and technical sides, including users, use case representatives, business owners, engineers, architects, and UI designers, to achieve end-to-end project goals and integrate into production Bachelor's Degree or equivalent Minimum of 5 years of experience as a machine learning engineer or scientist, deploying models in production at scale , including monitoring, alerting, automatic bug filing and auditing. Minimum of 5 years of experience in applying theoretical foundations of computer science, including computer system architecture, system engineering, and programming Minimum of 3 years of experience in distributed computing systems and architecture that may include big data, high-performance compute, engineering simulations, scientific compute, grid and cloud computing, distributed networks Minimum of 2 years of experience in building and deploying AI/ML based software to a cloud environment. Proficiency in Python and python-based AI/ML framework and familiarity with relevant libraries and frameworks (e.g., TensorFlow, PyTorch).. Experience working with language models like LLM's APIs and optimizing their usage for specific applications. Experience with the following programming languages: Python, C++, Java, R, SQL Strong written & verbal communication skills and ability to communicate complex technical concepts to non-technical stakeholders Strong client-facing skillsets in a consulting environment Strong cross-functional skills with the ability to collaborate with a variety of internal and client-side teams Entrepreneurial mindset with a curiosity and passion for emergent tech and driving innovation MS or PhD in related field preferred (computer science, engineering, etc.) As a Data Architect, a typical day involves defining the data requirements and structuring the data for various applications. This role includes designing and modeling the data architecture to ensure efficient storage and seamless integration across systems. The position requires a thoughtful approach to organizing data assets to support application functionality and business needs, while collaborating with different teams to align data strategies with project goals.
Project Role : Data Architect Project Role Description : Define the data requirements and structure for the application. Model and design the application data structure, storage and integration. Must have skills : Data Science Good to have skills : Snowflake Data Warehouse, Amazon Web Services (AWS) Minimum 12 year(s) of experience is required Educational Qualification : 15 years full time education Summary:
Roles & Responsibilities: - Expected to be an SME, collaborate and manage the team to perform. - Responsible for team decisions. - Engage with multiple teams and contribute on key decisions. - Expected to provide solutions to problems that apply across multiple teams. - Lead the development and implementation of data architecture standards and best practices. - Facilitate communication between technical teams and stakeholders to ensure data requirements are met. - Mentor junior team members to support their professional growth and enhance team capabilities. Professional & Technical Skills: - Must To Have Skills: Proficiency in Data Science. - Good To Have Skills: Experience with Snowflake Data Warehouse, Amazon Web Services (AWS). - Strong knowledge of data modeling techniques and database design principles. - Experience in designing scalable data storage solutions and data integration strategies. - Ability to analyze complex data flows and optimize data pipelines for performance and reliability. - Familiarity with cloud-based data platforms and modern data architecture frameworks. Additional Information: - The candidate should have minimum 12 years of experience in Data Science. - This position is based at our Pune office. - A 15 years full time education is required.
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Yes. We’ve followed 24 other Data Architect jobs there since October 2026. All 24 are still up.
Large employers often post one title for several teams, so these can be separate openings.
New ML Engineer postings at the employers we follow are up 10% over the last 6 weeks compared with the 6 before.
Each bar is one week of new postings. The darkest bars are the last 6 weeks.
Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.
We file this job under ML Engineer, by the work the posting describes.
ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.
Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.
A data scientist often works out which model to build; an ML engineer makes it run reliably in production.
The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.
About Accenture
Accenture is a leading global professional services company that helps the world’s leading businesses, governments and other organizations build their digital core, optimize their operations, accelerate revenue growth and enhance citizen services—creating tangible value at speed and scale. We are a talent- and innovation-led company with approximately 791,000 people serving clients in more than 120 countries. Technology is at the core of change today, and we are one of the world’s leaders in helping drive that change, with strong ecosystem relationships. We combine our strength in technology and leadership in cloud, data and AI with unmatched industry experience, functional expertise and global delivery capability. Our broad range of services, solutions and assets across Strategy & Consulting, Technology, Operations, Industry X and Song, together with our culture of shared success and commitment to creating 360° value, enable us to help our clients reinvent and build trusted, lasting relationships. We measure our success by the 360° value we create for our clients, each other, our shareholders, partners and communities.Visit us at www.accenture.com
Equal Employment Opportunity Statement
We believe that no one should be discriminated against because of their differences. All employment decisions shall be made without regard to age, race, creed, color, religion, sex, national origin, ancestry, disability status, military veteran status, sexual orientation, gender identity or expression, genetic information, marital status, citizenship status or any other basis as protected by applicable law. Our rich diversity makes us more innovative, more competitive, and more creative, which helps us better serve our clients and our communities.
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Pune
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