Manager – Deal Advisory – Deals Tech & Data Solutions (DTDS)

A career in our Deals RVD will provide you the opportunity to help organizations realize the potential of mergers, acquisitions and divestitures and capital markets. In short, we help some of the world’s leading companies originate, create, execute, and realize value from deals. Through data driven insights we help our clients move in the right direction ensuring maximum value for their company during separation/integration management. 

As a part of this team, you will gain exposure not only to the top Deals experts at PwC, but also engage with clients and industry analysts globally.  You will contribute to identify, shape and execute deals that accelerate client business strategies and capture significant value.

As part of our team of problem solvers, you will analyze clients’ data, assess Deal impact, aid in vendor negotiations, assist in buy-side and sell-side diligences across various phases of a deal lifecycle - pre-sign, sign-to-close and post close.  

Key Responsibilities: • Supervise, develop, and coach teams to deliver complex analytics solutions

• Analyze complex problems and provide actionable insights

• Automate repetitive data preparation, cleansing, and reporting tasks using AI-assisted pipelines and low-code/no-code tools.

• Leverage data visualization tools and programming languages

• Apply Generative AI tools for rapid data synthesis, drafting, and insight generation across various stages of a deal.

• Build and maintain scalable data pipelines and analytics workflows using platforms such as Databricks to accelerate due diligence, integration, and value creation analytics.

• Develop and implement machine learning models for transaction risk assessment, customer churn prediction, synergy estimation, and financial performance forecasting

• Partner with Private Equity deal teams to design and execute analytics solutions that drive investment decisions, operational improvements, and portfolio value creation. • Communicate effectively with business partners and technologists • Navigate multiple engagements and manage stakeholder expectations • Maintain exceptional standards in deliverables

• Build and nurture meaningful relationships with clients and US team members • Thrive in a collaborative, fast-paced team environment To Qualify for the Role,

You Must Have • Bachelor’s degree (B.E/B.Tech) in Computer Science, IT, Electronics & Communication, or Electrical Engineering (minimum 60%)

• Master’s degree in Accounting, Finance, Economics, Data Analytics/Science, Business Administration, or Management Information Systems preferred

• 10+ years of experience in Data & Technology, with at least 6 years in Deals M&A Tech & Data (preferably in Consulting)

• Strong proficiency in SQL, Python or R

• Proficiency in data engineering pipelines (e.g., Azure Synapse Analytics, Apache Airflow) and AI/ML platforms such as Databricks

• Proficiency with data visualization tools (Power BI, Tableau, QlikView)

• Experience with machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and natural language processing tools (e.g., spaCy, HuggingFace Transformers)

• Experience with Generative AI platforms (e.g., OpenAI API, Azure OpenAI, Claude, Google Gemini) for insight generation and business process automation • Experience integrating analytics with cloud-native AI services (AWS SageMaker, Azure ML, Google Vertex AI)

• Understanding of key financial statements and accounting principles

• Strong analytical thinking, problem-solving, and stakeholder communication skills

• Ability to manage multiple engagements and competing priorities

Good-to-Have Skills

• Consulting industry experience • Certifications in database programming (Databricks, MS SQL Server, Oracle) and/or data visualization tools (Power BI, Tableau)

• Certifications within cloud platforms (Azure, AWS, GCP)

• Expertise in Microsoft Power Platform for rapid application development

• Certifications in predictive modeling or machine learning platforms (Python, SAS, etc.)

• Experience designing and executing evaluation frameworks for AI/GenAI output, including relevance, coherence, accuracy, and bias assessment