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.
?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 Data and Analytics services will provide you with the opportunity to help organisations uncover enterprise insights and drive business results using smarter data analytics. We focus on a collection of organisational technology capabilities, including business intelligence, data management, and data assurance that help our clients drive innovation, growth, and change within their organisations to keep up with the changing nature of customers and technology. We make impactful decisions by mixing mind and machine to leverage data, understand and navigate risk, and help our clients gain a competitive edge.
Responsibilities:
About the Role: We are looking for a highly skilled Data Scientist who can work across the entire data science lifecycle--from feature engineering and model development to deployment and monitoring--using modern ML platforms. The ideal candidate will have hands-on experience with Azure Machine Learning, Databricks, and MLflow, and will be comfortable building scalable solutions for real-world business problems. What will you do: Data Preparation & Feature Engineering Collect, clean, and preprocess structured and unstructured data from multiple sources. Perform feature selection, transformation, and creation for optimal model performance. Model Development Design, train, and validate predictive and prescriptive models using advanced statistical and machine learning techniques. Experiment with algorithms for classification, regression, clustering, and NLP. Model Deployment & Monitoring Deploy models into production using MLflow and Azure ML pipelines. Implement model versioning, reproducibility, and automated retraining strategies. End-to-End ML Lifecycle Management Manage experiments, track metrics, and maintain model registry in MLflow. Ensure compliance with MLOps best practices for scalability and reliability. Collaboration & Communication Work closely with data engineers, business analysts, and stakeholders to translate business requirements into data-driven solutions. Present insights and recommendations through dashboards and reports.
Mandatory skill sets:
'Must have' knowledge, skills and experiences Technical Expertise Strong proficiency in Python (pandas, scikit-learn, PySpark) and SQL. Experience with Azure Machine Learning, Databricks, and MLflow. Solid understanding of MLOps principles and CI/CD for ML models.
Data Science & ML Hands-on experience in feature engineering, model selection, hyperparameter tuning. Familiarity with deep learning frameworks (TensorFlow, PyTorch) is a plus. Cloud & Big Data Knowledge of Azure services like Azure Data Lake, Azure Fabric, and Azure Functions. Experience working with large-scale data on distributed systems. Soft Skills Strong problem-solving and analytical skills. Excellent communication and stakeholder management abilities.
Preferred skill sets:
'Good to have' knowledge, skills and experiences Familiarity with data lake architectures and delta lake concepts Familiarity with Azure ML/Databricks ML
Years of experience required: 5-8 years
Education qualification:
o BE, B.Tech, ME, M,Tech, MBA, MCA (60% above)
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 Microsoft Azure, Python (Programming Language)
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
Available for Work Visa Sponsorship?
Government Clearance Required?
Job Posting End Date

Skills Required