Data Science - Traditional AI / ML - Senior Associate
Bengaluru · Senior
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Job description
Industry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
Senior AssociateJob Description & Summary
The Opportunity
Join our Acceleration Center India and help shape the future of business for our diverse client portfolio across geographies and jurisdictions. You’ll work at the heart of global teams across Advisory, Assurance, Tax and Business Services—solving real client challenges through connected collaboration. We’ll help you grow your skills so you can go further. With hands-on learning, cutting-edge tools and an inclusive culture, this is your opportunity to do inspiring work that makes a difference—every day.
As a Data Science - Traditional AI / ML - Senior Associate you will focus on advanced analytics and statistical methods to explore data, develop models, and create visualizations that help solve complex business problems and inform decision making, within our Data, Analytics & AI practice. As a Senior Associate you will analyze complex problems, manage assigned workstreams, build meaningful client connections, and guide junior team members while strengthening your technical skills, personal brand, and understanding of the broader business context. In this role at PwC, you will work on exploratory and descriptive analysis, statistical modeling, and data visualization in support of client service engagements, using a range of tools and methodologies to generate insights and recommendations.
Responsibilities
- Analyzing client business problems and translating exploratory findings into clear data science recommendations
- Building statistical models, machine learning workflows, and predictive solutions that address complex business questions
- Designing and refining data preparation, feature engineering, and model validation activities across project workstreams
- Interpreting structured and unstructured data sources to identify trends, patterns, and measurable drivers of performance
- Developing data visualizations and presentation materials that communicate findings to technical and nontechnical audiences
- Applying Python, R, SQL, and machine learning libraries to support experimentation, model tuning, and solution delivery
- Reviewing data quality, model inputs, and output logic to identify issues that affect analysis and recommendations
- Supporting client conversations by clarifying needs, documenting requirements, and adapting deliverables as priorities shift
- Guiding junior team members on analytical methods, problem solving approaches, and technical documentation
- Validating that work aligns with professional standards, project objectives, and data science methodologies
What You Must Have
- At least a Bachelor's degree
- At least 4 years of experience
- Oral and written proficiency in English required
What Sets You Apart
- Preference for at least one of the following fields of study: Artificial Intelligence and Robotics, Business Analytics, Computer and Information Science, Computer Engineering, Computer Programming, Data Processing/Analytics/Science, Engineering, Information Technology, Machine Learning, Management Information Systems, Mathematics, Statistics, Systems Engineering
- Demonstrating AI and machine learning project experience in client settings
- Applying statistical analysis to interpret data and shape recommendations
- Translating complex technical concepts into clear client conversations
- Supporting workstreams while mentoring junior team members
- Using Python, R, TensorFlow, or Scikit-learn for modeling
- Advanced ML Models
- Feature Engineering
- Model Optimization
- Statistical Rigor
- Data Visualization
- Hypothesis testing
- Problem-solving Framework
- Python/SQL
- Ensemble Methods
- Regression Analysis
- Classification Techniques
- Clustering Methods
- Model Validation
- A/B Testing
- Causal Inference
- Performance Analysis
- Reproducibility
- Documentation
- Mentoring Capability
- Cross-functional Communication
- Business Translation
Travel Requirements
Not SpecifiedJob Posting End Date
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