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. Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven decision making. You will work on developing predictive models, conducting statistical analysis, and creating data visualisations to solve complex business problems.

Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow.

Skills

Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to:

• Respond effectively to the diverse perspectives, needs, and feelings of others.
• Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems.
• Use critical thinking to break down complex concepts.
• Understand the broader objectives of your project or role and how your work fits into the overall strategy.
• Develop a deeper understanding of the business context and how it is changing.
• Use reflection to develop self awareness, enhance strengths and address development areas.
• Interpret data to inform insights and recommendations.
• Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements.
  
  

The Opportunity

When you join PwC Acceleration Centers (ACs), you step into a pivotal role focused on actively supporting various Acceleration Center services, from Advisory to Assurance, Tax and Business Services. In our innovative hubs, you’ll engage in challenging projects and provide distinctive services to support client engagements through enhanced quality and innovation. You’ll also participate in dynamic and digitally enabled training that is designed to grow your technical and professional skills.

As part of the Customer Link team you will apply data analytics and machine learning techniques to solve real-world client problems. As a Senior Associate you will build analytical models, derive insights from complex datasets, and leverage AI to enhance problem-solving while developing a deeper understanding of business contexts. This role emphasizes critical thinking and structured problem-solving, providing a platform to collaborate with cross-functional teams and engage with stakeholders effectively.

Responsibilities

• Apply data analytics and machine learning techniques to client challenges
• Build analytical models to derive insights from diverse datasets
• Leverage AI tools to enhance problem-solving capabilities
• Collaborate with cross-functional teams to drive project success
• Develop a deeper understanding of business contexts and needs
• Engage effectively with stakeholders to gather requirements
• Utilize critical thinking for structured problem-solving
• Maintain rigorous standards in analytical deliverables
  
  

What You Must Have

• Bachelor's or Master Degree from top-tier institutions (IITs/NITs/BITS)
• 4 years of experience in data science or analytics
• Oral and written proficiency in English required
  
  

What Sets You Apart

• Bachelor's or master's degree in Engineering, Statistics, or a related field
• 4+ years of experience in Python for data analysis and machine learning.
• Familiarity with AI techniques and prompt engineering
• Solid understanding of machine learning techniques and statistical analysis
• Exposure to PySpark and large-scale data environments
• Curiosity to explore new AI techniques
• Ability to think structurally and approach problems clearly
• Demonstrating ownership in fast-paced environments
• Excelling in collaboration and stakeholder management skills