Line of Service
AdvisoryIndustry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
Senior AssociateJob Description & 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.*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 about us.
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. "
Responsibilities
Design and implement scalable forecasting and predictive analytics models to solve complex business challenges across multiple domains.
Develop and optimize data models (logical, physical, dimensional, and semantic) to support analytics, ML, and reporting use cases.
Work with large, complex datasets from multiple sources—cleansing, transforming, and preparing them for analytical consumption.
Build, train, and evaluate ML models using statistical and machine learning techniques to enhance accuracy, performance, and interpretability.
Collaborate with data engineers and cloud teams to integrate ML pipelines into AWS or Azure environments using modern ETL and orchestration tools.
Translate business objectives into technical data solutions and actionable insights through strong analytical reasoning and stakeholder communication.
Ensure data quality, lineage, and consistency through standardized data definitions, metadata documentation, and model versioning practices.
Continuously improve models through retraining, drift detection, and performance monitoring using MLOps best practices.
Required Skills and Experience
Proven expertise in machine learning and statistical modeling for forecasting, demand prediction, or time-series analysis.
Strong data modeling skills across dimensional, relational, and semantic structures.
Advanced proficiency in Python for data wrangling, feature engineering, and ML model development (Pandas, NumPy, Scikit-learn, PyTorch/TensorFlow preferred).
Intermediate SQL skills with experience writing efficient queries and optimizing database performance.
Strong analytical and problem-solving mindset with the ability to derive insights and communicate outcomes to technical and business stakeholders.
Mandatory Skill Sets:
Domain experience in retail, supply chain, demand forecasting, or CPG analytics.
Strong interest in emerging areas such as Generative AI or AI-driven forecasting automation.
Exposure to cloud ecosystems (AWS, Azure) including data engineering components like Glue, Data Factory, Lambda, Databricks, or Synapse.
Preferred Skill Sets:
Domain experience in retail, supply chain, demand forecasting, or CPG analytics.
Strong interest in emerging areas such as Generative AI or AI-driven forecasting automation.
Exposure to cloud ecosystems (AWS, Azure) including data engineering components like Glue, Data Factory, Lambda, Databricks, or Synapse.
Years of Experience required:
Senior Associate – 4 to 7 years
Education Qualification:
B.E, B.Tech, M.Tech, M.E, MCA
Education (if blank, degree and/or field of study not specified)
Degrees/Field of Study required: Master of Engineering, Bachelor of EngineeringDegrees/Field of Study preferred:Certifications (if blank, certifications not specified)
Required Skills
Data ScienceOptional 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 SpecifiedAvailable for Work Visa Sponsorship?
NoGovernment Clearance Required?
NoJob Posting End Date
May 5, 2026