Senior Associate AWS Architect

Role Overview: As a Senior Associate in the Advisory sector at PwC specializing in Data, Analytics & AI, you will be instrumental in leveraging advanced technologies and techniques to design and develop robust data solutions for clients. Your role will involve transforming raw data into actionable insights, facilitating informed decision-making, and driving business growth through innovative data engineering strategies. Key Responsibilities: - Develop a deep understanding of different types of data, metrics, and KPIs to identify and formulate data science problems that drive impactful solutions. - Utilize proficiency in Python/PySpark for AI development, data preprocessing, and scripting. - Apply a strong understanding of core machine learning and statistical concepts, including supervised, unsupervised, and reinforcement learning, feature engineering, and model optimization. - Hands-on experience in building, training, and deploying ML models for various use cases such as prediction, recommendation, NLP, and computer vision. - Utilize proficiency in Python and machine learning libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, and Hugging Face Transformers. - Familiarity with deep learning architectures like CNNs, RNNs, Transformers, and their use cases in NLP, CV, and recommendation systems. - Experience in data preprocessing, feature selection, model evaluation, and hyperparameter tuning techniques. - Design and deploy scalable ML pipelines leveraging cloud platforms, preferably AWS, with Azure experience also being acceptable. - Familiarity with API development, microservices, and integrating ML models into enterprise applications. - Understand data security, governance, and cost optimization in cloud-based AI environments. - Experience in AWS AI and ML services, including SageMaker, Lambda, Step Functions, API Gateway, and CloudWatch for model deployment and orchestration. - Ability to work with containerization tools like Docker and Kubernetes for deploying ML workloads. Qualifications Required: - Mandatory skill sets include expertise in Machine Learning (ML) and Azure/AWS. - The ideal candidate should possess 4 - 7 years of experience in the field. - Education qualification required includes a Btech/MBA/MCA degree, with preferred degrees/field of study being Bachelor of Engineering or Master of Engineering. Additional Company Details: At PwC, you will have the opportunity to be part of a purpose-led and values-driven work environment, supported by technology and innovation. The company promotes equal employment opportunities, diversity, and inclusion, fostering an environment where individuals can contribute to their personal and professional growth. PwC maintains a zero-tolerance policy for discrimination and harassment based on various factors. Role Overview: As a Senior Associate in the Advisory sector at PwC specializing in Data, Analytics & AI, you will be instrumental in leveraging advanced technologies and techniques to design and develop robust data solutions for clients. Your role will involve transforming raw data into actionable insights, facilitating informed decision-making, and driving business growth through innovative data engineering strategies. Key Responsibilities: - Develop a deep understanding of different types of data, metrics, and KPIs to identify and formulate data science problems that drive impactful solutions. - Utilize proficiency in Python/PySpark for AI development, data preprocessing, and scripting. - Apply a strong understanding of core machine learning and statistical concepts, including supervised, unsupervised, and reinforcement learning, feature engineering, and model optimization. - Hands-on experience in building, training, and deploying ML models for various use cases such as prediction, recommendation, NLP, and computer vision. - Utilize proficiency in Python and machine learning libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, and Hugging Face Transformers. - Familiarity with deep learning architectures like CNNs, RNNs, Transformers, and their use cases in NLP, CV, and recommendation systems. - Experience in data preprocessing, feature selection, model evaluation, and hyperparameter tuning techniques. - Design and deploy scalable ML pipelines leveraging cloud platforms, preferably AWS, with Azure experience also being acceptable. - Familiarity with API development, microservices, and integrating ML models into enterprise applications. - Understand data security, governance, and cost optimization in cloud-based AI environments. - Experience in AWS AI and ML services, including SageMaker, Lambda, Step Functions, API Gateway, and CloudWatch for model deployment and orchestration. - Ability to work with containerization tools like Docker and Kubernetes for deploying ML workloads. Qualifications Required: - Mandatory skill sets include expertise in Machine Learning (ML) and Azure/AWS. - The ideal candidate should possess 4 - 7 years o