דרושים Det-azure Data Lead-gdsn02 ב-Ey ב-India, Thiruvananthapuram

Job Description: EY GDS – Data and Analytics (D&A) – Sr.Manager – Data Scientist

We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 14+ years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.

Your technical responsibilities:

• Contribute to the design and implementation of state-of-the-art AI solutions.
• Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
• Collaborate with stakeholders to identify business opportunities and define AI project goals.
• Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
• Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
• Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
• Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
• Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
• Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
• Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
• Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
• Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
• Ensure compliance with data privacy, security, and ethical considerations in AI applications.
• Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
• Minimum 14+ years of experience in Data Science and Machine Learning.
• In-depth knowledge of machine learning, deep learning, and generative AI techniques.
• Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
• Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
• Familiarity with computer vision techniques for image recognition, object detection, or image generation.
• Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
• Expertise in data engineering, including data curation, cleaning, and preprocessing.
• Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
• Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
• Understanding of data privacy, security, and ethical considerations in AI applications.
• Track record of driving innovation and staying updated with the latest AI research and advancements.

Good to Have Skills:

• Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
• Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
• Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
• Implement CI/CD pipelines for streamlined model deployment and scaling processes.
• Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
• Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
• Implement monitoring and logging tools to ensure AI model performance and reliability.
• Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
• Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

:EY GDS – Data and Analytics (D And A) – Senior – Senior Data Scientist

We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 3 - 7 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.

Your technical responsibilities:

• Contribute to the design and implementation of state-of-the-art AI solutions.
• Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
• Collaborate with stakeholders to identify business opportunities and define AI project goals.
• Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
• Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
• Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
• Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
• Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
• Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
• Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
• Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
• Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
• Ensure compliance with data privacy, security, and ethical considerations in AI applications.
• Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
• Minimum 3-7 years of experience in Data Science and Machine Learning.
• In-depth knowledge of machine learning, deep learning, and generative AI techniques.
• Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
• Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
• Familiarity with computer vision techniques for image recognition, object detection, or image generation.
• Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
• Expertise in data engineering, including data curation, cleaning, and preprocessing.
• Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
• Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
• Understanding of data privacy, security, and ethical considerations in AI applications.
• Track record of driving innovation and staying updated with the latest AI research and advancements.

Good to Have Skills:

• Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
• Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
• Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
• Implement CI/CD pipelines for streamlined model deployment and scaling processes.
• Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
• Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
• Implement monitoring and logging tools to ensure AI model performance and reliability.
• Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
• Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.

Global Managed Service – Identity and access Management – Staff

As a Azure AD Operations Support Specialist, you will be responsible for providing first-level support and maintenance of our Azure Active Directory environment. You will assist in managing user accounts, permissions, and access rights in accordance with company policies and regulatory requirements.

Key Requirements / Responsibilities:

• Provide first-level support for Azure Active Directory issues, including user account management, group management, and access control.
• Assist in the creation, modification, and deletion of user accounts and groups as per the requests and in compliance with the security policies.
• Monitor Azure AD health and performance, responding to alerts and notifications.
• Help in troubleshooting and resolving authentication and authorization issues.
• Support the implementation of Azure AD policies, Conditional Access policies, and Multi-Factor Authentication (MFA).
• Collaborate with the security team to ensure compliance with governance policies and audit requirements.
• Document operational procedures and issue resolution steps.
• Participate in the on-call rotation for after-hours support as needed.
• Stay current with Microsoft Azure updates and new features
• Monitor Azure AD services, ensuring uptime and availability, and proactively address any issues that arise
• Assist with the management of user identities, groups, and role-based access control (RBAC) within Azure AD.
• Respond to and resolve service tickets related to Azure AD, including user access issues, group membership changes, and application access problems.
• Participate in the onboarding and offboarding of employees, ensuring proper access is granted and revoked in a timely manner.
• Provide training and support to end-users on Azure AD-related services and features.
• Stay up-to-date with the latest Azure AD features and updates to provide recommendations for improvements.
• Maintain documentation for Azure AD processes and operational procedures.

Preferred Skills:

• Experience in IAM operations, with a strong emphasis on Azure AD and related Microsoft identity solutions.
• Demonstrated experience in operational support, incident management, and problem-solving within an IAM context.
• In-depth knowledge of cloud security, IAM protocols, and regulatory compliance requirements.
• Strong analytical, troubleshooting, and decision-making skills.
• Relevant certifications such as Microsoft Certified: Identity and Access Administrator Associate, ITIL, or similar
• Proficiency with scripting and automation tools (e.g., PowerShell, Azure CLI) to streamline operational tasks.

Bachelor’s degree in computer science, Information Technology, Cybersecurity, or a related field.

Work Requirements:

• Willingness to travel as required
• Willingness to be on call support engineer and work occasional overtime as required
• Willingness to work in shifts as required

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Role Overview:

We are seeking a highly skilled and experienced Senior Data Scientist with a minimum of 8 - 11 years of experience in Data Science and Machine Learning, preferably with experience in NLP, Generative AI, LLMs, MLOps, Optimization techniques, and AI solution Architecture. In this role, you will play a key role in the development and implementation of AI solutions, leveraging your technical expertise. The ideal candidate should have a deep understanding of AI technologies and experience in designing and implementing cutting-edge AI models and systems. Additionally, expertise in data engineering, DevOps, and MLOps practices will be valuable in this role.

Your technical responsibilities:

• Contribute to the design and implementation of state-of-the-art AI solutions.
• Assist in the development and implementation of AI models and systems, leveraging techniques such as Language Models (LLMs) and generative AI.
• Collaborate with stakeholders to identify business opportunities and define AI project goals.
• Stay updated with the latest advancements in generative AI techniques, such as LLMs, and evaluate their potential applications in solving enterprise challenges.
• Utilize generative AI techniques, such as LLMs, to develop innovative solutions for enterprise industry use cases.
• Integrate with relevant APIs and libraries, such as Azure Open AI GPT models and Hugging Face Transformers, to leverage pre-trained models and enhance generative AI capabilities.
• Implement and optimize end-to-end pipelines for generative AI projects, ensuring seamless data processing and model deployment.
• Utilize vector databases, such as Redis, and NoSQL databases to efficiently handle large-scale generative AI datasets and outputs.
• Implement similarity search algorithms and techniques to enable efficient and accurate retrieval of relevant information from generative AI outputs.
• Collaborate with domain experts, stakeholders, and clients to understand specific business requirements and tailor generative AI solutions accordingly.
• Conduct research and evaluation of advanced AI techniques, including transfer learning, domain adaptation, and model compression, to enhance performance and efficiency.
• Establish evaluation metrics and methodologies to assess the quality, coherence, and relevance of generative AI outputs for enterprise industry use cases.
• Ensure compliance with data privacy, security, and ethical considerations in AI applications.
• Leverage data engineering skills to curate, clean, and preprocess large-scale datasets for generative AI applications.

Requirements:

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field. A Ph.D. is a plus.
• Minimum 8-11 years of experience in Data Science and Machine Learning.
• In-depth knowledge of machine learning, deep learning, and generative AI techniques.
• Proficiency in programming languages such as Python, R, and frameworks like TensorFlow or PyTorch.
• Strong understanding of NLP techniques and frameworks such as BERT, GPT, or Transformer models.
• Familiarity with computer vision techniques for image recognition, object detection, or image generation.
• Experience with cloud platforms such as Azure, AWS, or GCP and deploying AI solutions in a cloud environment.
• Expertise in data engineering, including data curation, cleaning, and preprocessing.
• Knowledge of trusted AI practices, ensuring fairness, transparency, and accountability in AI models and systems.
• Strong collaboration with software engineering and operations teams to ensure seamless integration and deployment of AI models.
• Excellent problem-solving and analytical skills, with the ability to translate business requirements into technical solutions.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with stakeholders at various levels.
• Understanding of data privacy, security, and ethical considerations in AI applications.
• Track record of driving innovation and staying updated with the latest AI research and advancements.

Good to Have Skills:

• Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.
• Utilize optimization tools and techniques, including MIP (Mixed Integer Programming).
• Drive DevOps and MLOps practices, covering continuous integration, deployment, and monitoring of AI models.
• Implement CI/CD pipelines for streamlined model deployment and scaling processes.
• Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.
• Apply infrastructure as code (IaC) principles, employing tools like Terraform or CloudFormation.
• Implement monitoring and logging tools to ensure AI model performance and reliability.
• Collaborate seamlessly with software engineering and operations teams for efficient AI model integration and deployment.
• Familiarity with DevOps and MLOps practices, including continuous integration, deployment, and monitoring of AI models.

Key Responsibilities:

The role requires strong expertise in BI/Visualization practice using Power BI, the candidate must have strong ability to:

• Lead and mentor a team throughout design, development and delivery phases and keep the team intact on high pressure situations.
• Working with the clients directly to understand the requirement and determine the optimum solutions
• Create technical solutions as per business needs by translating their requirements and finding innovative solution options
• Provide product and design level functional and technical expertise along with best practices
• Work both as a good team player and an individual contributor throughout design, development and delivery phases and stay with the focussed on the quality of the deliverable.
• Demonstrate willingness to upskill and take on new challenges
• Ability to quickly do POCs and demonstrate solutions to the client/onshore teams
• Get involved in business development activities like creating POCs, assist in RFPs, service offering development etc.
• Participate in organization-level initiatives & operational activities
• Ensure continual knowledge management and contribute to internal L&D teams

Qualifications:

BE/BTech/MCA/MBA with 3 - 5 years industry experience

Must have:

• PowerBI hands-on experience for a minimum of 3-5 years
• Strong proficiency in SQL/PLSQL
• Good experience in performance tuning reports and dashboards.
• Excellent communication skills to interact with and present solutions to stakeholders

Good to have:

• Working knowledge on other reporting tools like Tableau
• Good knowledge about data concepts such as Data Warehouses, Data Marts, data extraction, preparation processes
• Understanding of the importance of data governance and data security
• Experience on Banking and Capital Markets domains

People responsibilities:

• Prior Client facing skills and proven ability in effective planning, executing and problem-solving skills
• Multi-tasking attitude, flexible with ability to change priorities quickly
• Ability to plan resource requirements from high level specifications
• Ability to quickly understand and learn new technology/feature and should inspire change to make an impact within the team and in a client organisation

EY exists to build a better working world, helping to create long-term value for clients, people and society and build trust in the capital markets.

Azure ML and Python Dev- Senior 1/2

EY GDS Consulting digital engineering, is seeking experienced Azure ML and Python Developer. Your responsibilities will include designing and implementing data pre-processing, feature engineering, and model training pipelines, collaborating closely with data scientists, and ensuring model performance and reliability in production environments. Proficiency in Azure ML services, Python programming, and a strong background in machine learning are key requirements for this role.

Your key responsibilities

• Develop and deploy machine learning models on Azure cloud platform using Python programming language and Azure ML services.
• Design and implement scalable and efficient data pipelines for model training and inference.
• Collaborate with data scientists and business stakeholders to understand requirements and translate them into technical solutions.
• Implement best practices for ML development, including version control, testing, and documentation.
• Develop and maintain APIs on Azure cloud platform for model deployment and integration with applications.
• Monitor and optimize model performance, ensuring scalability, reliability, and security.
• Participate in code reviews, troubleshooting, and optimization to improve performance and maintainability.
• Stay updated with industry trends and best practices in machine learning, cloud computing, and API development.
• Mentor junior team members, sharing expertise and guiding them in technical challenges.
• Collaborate with cross-functional teams, including data engineers, data scientists, and business analysts, to deliver end-to-end solutions.
• Conduct regular evaluations and assessments of ML models and APIs, identifying areas for improvement and optimization.
• Lead and contribute to innovation initiatives, exploring new technologies and approaches to enhance our ML and cloud capabilities.

Soft Skills

• Bachelor's degree in computer science, data science, or related field.
• 6-8 years of experience in machine learning, data engineering, and cloud computing, with a strong focus on Azure services.
• Proficiency in Python programming language for ML model development and deployment.
• Experience with Azure ML services, Azure data services (e.g., Azure Data Lake, Azure SQL Database), and Azure cloud infrastructure.
• Strong understanding of machine learning concepts, algorithms, and techniques, including supervised and unsupervised learning, deep learning, and natural language processing.
• Expertise in designing and implementing data pipelines for ML model training and inference, using tools like Azure Databricks, Azure Data Factory, and Azure Synapse Analytics.
• Familiarity with cloud-native technologies, containerization (e.g., Docker, Kubernetes), and DevOps practices for ML model deployment and automation.
• Experience with version control systems (e.g., Git/GitHub), CI/CD pipelines, and software engineering best practices for ML projects.
• Strong analytical and problem-solving skills, with the ability to analyze complex data sets, identify patterns, and derive meaningful insights.
• Excellent communication and collaboration skills, with the ability to work effectively in cross-functional teams and communicate technical concepts to non-technical stakeholders.
• Proactive mindset, self-driven, and eager to learn new technologies and methodologies in the ML and cloud computing space.
• Ability to work in a fast-paced environment, manage multiple priorities, and deliver high-quality results under tight deadlines.

To qualify for the role, you must have

• A bachelor's or master's degree in computer science, data science, or related field.
• 6-8 years of hands-on experience in machine learning, cloud computing, and API development, with a focus on Azure services.
• Proficiency in Python programming language for ML model development and deployment, along with experience using Azure ML services and Azure cloud infrastructure.
• Strong communication skills, both verbal and written, with the ability to articulate technical concepts effectively to diverse audiences.
• Proven track record of successfully delivering ML projects, designing scalable data pipelines, and collaborating in cross-functional teams.
• Certifications such as Microsoft Certified: Azure AI Engineer Associate, Microsoft Certified: Azure Data Scientist Associate, or equivalent, are highly desirable.
• Experience with other cloud platforms (e.g., AWS, Google Cloud Platform) and additional programming languages (e.g., R, Java) is a plus.

Ideally, you’ll also have

• Analytical ability to manage multiple ML projects simultaneously, prioritize tasks effectively, and make data-driven decisions.
• Experience operating independently or with minimal supervision, demonstrating strong problem-solving skills and initiative.
• Familiarity with advanced ML techniques and frameworks (e.g., TensorFlow, PyTorch) for deep learning and computer vision applications.
• Knowledge of cloud security principles, data governance, and regulatory compliance frameworks relevant to ML and cloud environments.
• Experience with Big Data technologies (e.g., Apache Spark, Hadoop) for processing large-scale datasets and building ML models at scale.

You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer:

• Support, coaching and feedback from some of the most engaging colleagues around
• Opportunities to develop new skills and progress your career
• The freedom and flexibility to handle your role in a way that’s right for you

To qualify for the role, you must have

We are looking for a Data Engineer with 5-10 years of experience in data warehousing, ETL/ELT processes, data modeling, and cloud-based technologies, particularly Azure and Fabric. The ideal candidate will have a strong background in building and managing data solutions within the Microsoft Fabric platform and will be proficient in various programming languages.

Your key responsibilities

• Design, develop, and manage data solutions using Microsoft Fabric, including Lakehouse, Data Engineering, Pipelines, Spark, Notebooks, and KQL Database.
• Implement ETL/ELT processes to ensure efficient data integration and transformation.
• Create and maintain data models to support business intelligence and analytics initiatives.
• Utilize Azure data storage services (e.g., Azure SQL Database, Azure Blob Storage, Azure Data Lake Storage) for effective data management.
• Collaborate with cross-functional teams to gather requirements and deliver data solutions that meet business needs.
• Write and optimize code in SQL, Python, PySpark, and Scala for data processing and analysis.
• Implement DevOps practices and CI/CD pipelines for seamless data deployment and version control.
• Monitor and troubleshoot data pipelines to ensure reliability and performance.
• Communicate effectively with diverse teams to foster collaboration and knowledge sharing.

Ideally, you’ll also have

Client management skills

What we look for

People with technical experience and enthusiasm to learn new things in this fast-moving environment

You get to work with inspiring and meaningful projects. Our focus is education and coaching alongside practical experience to ensure your personal development. We value our employees and you will be able to control your own development with an individual progression plan. You will quickly grow into a responsible role with challenging and stimulating assignments. Moreover, you will be part of an interdisciplinary environment that emphasizes high quality and knowledge exchange. Plus, we offer:

• Support, coaching and feedback from some of the most engaging colleagues around
• Opportunities to develop new skills and progress your career
• The freedom and flexibility to handle your role in a way that’s right for you