Data Science - Traditional AI / ML - Manager
At a glance
Manager-level Data Science role at Pwc (Crm Experienced Careers Site). Bangalore · full-time.
Pay not stated Data Science salary
dataroles summary, based on the employer's posting.
What you'll do
- Lead analytics workstreams that use traditional AI and machine learning to address client business questions
- Plan project budgets, schedules and outputs across multiple analytics engagements
- Build statistical and predictive models, then turn complex datasets into useful business insights
- Review modeling processes, results and documentation for sound, consistent delivery
- Coach team members, assess model performance and present practical recommendations to clients
What you bring
- You hold at least a bachelor's degree and bring eight or more years of experience
- You can communicate in English in both written and spoken settings
Who this fits
This manager role suits someone who can lead AI and machine learning delivery while guiding team members and project execution. You’ll work with client stakeholders and manage several analytics workstreams.
From the employer
Industry/Sector
Not ApplicableSpecialism
Data, Analytics & AIManagement Level
ManagerJob 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 - Manager you will lead client support work in data science, applying advanced analytics and statistical methods to explore data, build models, and communicate insights that inform business decisions. As a Manager you will motivate and coach team members, guide project execution, and validate deliverables across multiple workstreams while bringing business awareness and integrity to client service. In this role at PwC, you will shape data-driven solutions within our Data and Analytics Engineering practice, support exploratory and descriptive analysis, develop visualizations, and help translate complex business problems into practical analytical approaches.
Responsibilities
- Leading data science workstreams that apply traditional AI and machine learning methods to client business problems
- Managing project planning, budgets, timelines, and deliverables across multiple analytics engagements
- Developing statistical models, predictive solutions, and descriptive analyses that translate complex data into actionable insights
- Reviewing data science workflows, model outputs, and documentation to support consistency and technical rigor
- Coaching team members on data modeling, machine learning techniques, and effective use of analytics tooling
- Applying Python, R, TensorFlow, Scikit-learn, and related programming languages to build and refine models
- Working through data preparation, feature engineering, model testing, and performance evaluation across varied datasets
- Presenting findings and recommendations to client stakeholders in a clear, business-focused manner
- Identifying opportunities to improve data quality, automation, and analytical methods within client environments
What You Must Have
- At least a Bachelor's degree
- At least 8 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 experience leading AI and machine learning delivery teams
- Applying statistical analysis to complex business and client data
- Managing project planning, budgeting, execution, and timelines
- Coaching team members through model development and review cycles
- Translating technical findings into client-ready recommendations
- Using AI fluency and data-driven decision making in delivery
- Advanced ML Algorithms
- Feature Engineering Strategy
- Model Optimization
- Statistical Frameworks
- Experimental Design
- MLflow Integration
Travel Requirements
Not SpecifiedJob Posting End Date