Deal Data Technology & Analytics, Senior Associate

Industry/Sector
Not Applicable

Specialism
Deals

Management Level
Senior Associate

Job Description & Summary
At PwC, our people in data and analytics focus on leveraging data to drive insights and make informed business decisions. They utilise advanced analytics techniques to help clients optimise their operations and achieve their strategic goals.

In Deals; data analysis at PwC, you will focus on utilising advanced analytical techniques to extract insights from large datasets and drive data-driven decision-making. You will leverage skills in data manipulation, visualisation, and statistical modelling to support clients in solving 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.

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

As part of the Deals (M&A) Tech & Data team you are expected to build tech-enabled business solutions and communicate with both technologists and business partners. As a Senior Associate you are expected to analyze complex problems, mentor others, and maintain rigorous standards. You are expected to navigate multiple engagements, manage stakeholder expectations, and leverage data visualization tools and programming languages to derive insights.

You will have the opportunity to harness modern technologies, data engineering, Generative AI, and advanced analytical techniques to deliver differentiated insights in complex M&A scenarios. You will help clients with their broad AI strategy and use case development. You will experiment with and deploy emerging AI tools for structured and unstructured data extraction, scenario modeling, automated reporting, and client storytelling-turning complex deal data into compelling, actionable narratives.

You will work closely with leading Private Equity clients and management of their portfolio companies, applying advanced analytics and emerging technologies to evaluate investment opportunities, assess risk, and improve portfolio company performance in a fact-driven, data-powered way.

Responsibilities

- 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

- Working 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 stakeholders and technologists

- Mentor and guide junior team members

- Build and nurture meaningful client relationships

What You Must Have

- Bachelor's Degree in Computer Science, Data Processing/Analytics/Science, Applied Mathematics, Statistics, Business Analytics, Finance, Accounting, Economics, Management Information Systems, Engineering

- 3 years of experience in the data and technology space

What Sets You Apart

- Master's Degree preferred

- Proficient in programming languages such as SQL, Python or R, with experience in machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and natural language processing tools (e.g., spaCy, HuggingFace Transformers)

- Familiarity with data engineering pipelines (e.g., Azure Synapse Analytics, dbt, Apache Airflow) and AI/ML platforms such as Databricks, including experience with collaborative notebooks and scalable data processing

- Experience using Generative AI platforms (e.g., OpenAI API, Azure OpenAI, Claude, Google Gemini) for business process enhancement and insight generation

- Experience integrating analytics with cloud-native AI services (AWS SageMaker, Azure ML, Google Vertex AI)

- Consulting Industry experience

- Certifications in database programming such as Databricks, MS SQL Server, etc. and/or data visualization certifications such as PowerBI

- Experience with relational database models and writing Python/SQL queries

- Experience with data storytelling-turning analytical output into persuasive visual and narrative formats for senior stakeholders

- Proficiency with data visualization tools (e.g. Power BI, Tableau)

- Ability to prototype and iterate rapidly using modern analytics and AI tools, balancing speed with rigor

- Certifications within cloud technology platforms such as AWS, Azure, GCP, etc.

- Certifications within predictive modeling and/or machine learning platforms such as Python, SAS, etc.

- Proven track record of deploying AI/ML solutions in live business environments, ideally in M&A or transaction contexts

- Understanding of key financial statements and accounting principles

- Critical thinking and problem-solving capabilities

- Ability to navigate multiple engagements and competing priorities

Travel Requirements
Up to 20%

Job Posting End Date

The salary range for this position is: $77,000 - $202,000. Actual compensation within the range will be dependent upon the individual's skills, experience, qualifications and location, and applicable employment laws. All hired individuals are eligible for an annual discretionary bonus. PwC offers a wide range of benefits, including medical, dental, vision, 401k, holiday pay, vacation, personal and family sick leave, and more. To view our benefits at a glance, please visit the following link:

As PwC is an equal opportunity employer, all qualified applicants will receive consideration for employment at PwC without regard to race; color; religion; national origin; sex (including pregnancy, sexual orientation, and gender identity); age; disability; genetic information (including family medical history); veteran, marital, or citizenship status; or, any other status protected by law.


PwC does not intend to hire experienced or entry level job seekers who will need, now or in the future, PwC sponsorship through the H-1B lottery, except as set forth within the following policy:

Learn more about how we work:

For only those qualified applicants that are impacted by the Los Angeles County Fair Chance Ordinance for Employers, the Los Angeles' Fair Chance Initiative for Hiring Ordinance, the San Francisco Fair Chance Ordinance, San Diego County Fair Chance Ordinance, and the California Fair Chance Act, where applicable, arrest or conviction records will be considered for Employment in accordance with these laws. At PwC, we recognize that conviction records may have a direct, adverse, and negative relationship to responsibilities such as accessing sensitive company or customer information, handling proprietary assets, or collaborating closely with team members. We evaluate these factors thoughtfully to establish a secure and trusted workplace for all.