Job Description

Line of Service Advisory
Industry/Sector Not Applicable
Specialism Data, Analytics & AI
Management Level Senior Associate
& Summary At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth.
In data engineering at PwC, you will focus on designing and building data infrastructure and systems to enable efficient data processing and analysis. You will be responsible for developing and implementing data pipelines, data integration, and data transformation solutions.
Why PWC
At PwC, you will be part of a vibrant community of solvers that leads with trust and creates distinctive outcomes for our clients and communities. This purpose-led and values-driven work, powered by technology in an environment that drives innovation, will enable you to make a tangible impact in the real world. We reward your contributions, support your wellbeing, and offer inclusive benefits, flexibility programmes and mentorship that will help you thrive in work and life. Together, we grow, learn, care, collaborate, and create a future of infinite experiences for each other. Learn more .
At PwC, we believe in providing equal employment opportunities, without any discrimination on the grounds of gender, ethnic background, age, disability, marital status, sexual orientation, pregnancy, gender identity or expression, religion or other beliefs, perceived differences and status protected by law. We strive to create an environment where each one of our people can bring their true selves and contribute to their personal growth and the firm's growth. To enable this, we have zero tolerance for any discrimination and harassment based on the above considerations. "
& Summary: A career within....
Responsibilities:

• Develop a deep understanding of different types of data, metrics, and KPIs to identify and formulate data science problems that drive impactful solutions. o Proficiency in Python/PySpark for AI development, data preprocessing, and scripting. o Strong understanding of core machine learning and statistical concepts -- including supervised, unsupervised, and reinforcement learning, feature engineering, and model optimization. o Hands-on experience in building, training, and deploying ML models for use cases such as prediction, recommendation, NLP, and computer vision. o Proficiency in Python and machine learning libraries such as scikit-learn, TensorFlow, PyTorch, XGBoost, and Hugging Face Transformers. o Familiarity with deep learning architectures -- CNNs, RNNs, Transformers -- and use cases in NLP, CV, and recommendation systems. o Experience with data preprocessing, feature selection, model evaluation, and hyperparameter tuning techniques. o Ability to design and deploy scalable ML pipelines leveraging cloud platforms -- preferably AWS, but Azure experience is also acceptable. o Familiarity with API development, microservices, and integrating ML models into enterprise applications.

• Understanding of data security, governance, and cost optimization in cloud-based AI environments. o Experience in AWS AI and ML services, including SageMaker, Lambda, Step Functions, API Gateway, and CloudWatch, for model deployment and orchestration. o Ability to work with containerization tools (Docker, Kubernetes) for deploying ML workloads.

Mandatory skill sets:
ML & Azure/AWS
Preferred skill sets:
MLOps frameworks (MLflow, Kubeflow, or Vertex AI Pipelines).
Years of experience required:
4 - 7 yrs
Education qualification:
Btech/MBA/MCA
Education (if blank, degree and/or field of study not specified) Degrees/Field of Study required: Master of Engineering, Bachelor of Engineering
Degrees/Field of Study preferred:
Certifications (if blank, certifications not specified)
Required Skills Machine Learning (ML)
Optional Skills Accepting Feedback, Accepting Feedback, Active Listening, Agile Scalability, Amazon Web Services (AWS), Analytical Thinking, Apache Airflow, Apache Hadoop, Azure Data Factory, Communication, Creativity, Data Anonymization, Data Architecture, Database Administration, Database Management System (DBMS), Database Optimization, Database Security Best Practices, Databricks Unified Data Analytics Platform, Data Engineering, Data Engineering Platforms, Data Infrastructure, Data Integration, Data Lake, Data Modeling, Data Pipeline {+ 27 more}
Desired Languages (If blank, desired languages not specified)
Travel Requirements Not Specified
Available for Work Visa Sponsorship? No
Government Clearance Required? No
Job Posting End Date

Skills Required