Data Strategy and Management - Private Equity Sector - Senior - Consulting - Location OPEN

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Private Equity Data and Analytics – Senior  

 

Private equity (PE) firms, portfolio companies and investment funds are under pressure to deploy capital and create value amid unprecedented economic and geopolitical uncertainty, increased competition, and rising stakeholder expectations. Success depends on the ability to move faster, drive rapid and strategic growth and create greater value.  

 

EY delivers advisory and implementation work to our clients in the PE sector, leveraging a breadth of experience from our Technical Consulting, Business Consulting, and Strategy and Transactions businesses. 

 

From data strategy and roadmaps, enterprise data management, data lake/warehouse implementation, deal metrics delivery, and LLM use case delivery, the EY PE Data and Analytics team leverages the latest technologies to accelerate value creation for our clients.  

 

The opportunity 

EY professionals help unlock and cultivate value with fit-for-purpose solutions throughout the private equity investment life cycle, supporting stronger, more resilient companies to achieve their purpose and long-term value aspirations. Our Data and Analytics teams help organizations apply advanced analytics techniques to drive competitive advantage, use advanced learning algorithms to solve complex business problems and create differentiated value, and generate insights by capturing data from machines and devises in near real-time. 

 

As a member of our Private Equity sector team, you will help private equity backed companies and their Sponsors navigate the complex world of modern data management, data engineering, data science, analytics, and emerging technologies.  We will look to you to bring cross-sector industry experience and knowledge about client’s data and analytics related problems, and help deliver solutions, go-to-market approaches and assist in solving the most critical business problems for our clients. This is a high growth, high visibility area with plenty of opportunities to enhance your skillset and build your career. 

 

Your key responsibilities 

You will work closely with our Strategy and Transactions and Consulting teams to understand the Private Equity Firm’s investment thesis and deal hypothesis to help deliver differentiated value for the portfolio company and its Sponsor. As a data and analytics PE sector Senior you will: 

 

• Be knowledgeable on the latest technologies, products and approaches related to modern data management (data fabric, data mesh, data products, etc…), data engineering practices and Analytics and AI execution 

• Execute project workstreams, support pursuit activities and coordinate with teams in translating business problems to analytical solutions and insights 

• Help our clients make data-driven decisions by utilizing structured and unstructured data in analysis to produce insights leveraging both basic and advanced analytics approaches 

• Assist teams in the execution of compelling sales materials, proposals, and presentations for presenting business focused data related solution to clients  

• Clearly communicate findings, recommendations and opportunities to improve data systems and solutions 

• Seek out information to learn about emerging methodologies and technologies 

• Collaborate, influence and build consensus through constructive relationships and effective listening across functional and sector teams 

• Support brainstorming sessions and workshops with business, technology, sector, industry, and executive teams on data related topics for developing data assessments, project execution plans, roadmaps, and action plans 

• Leverage a network of external partners and alliance partners for developing cutting edge solutions to solve our client’s business problems 

 

Skills and attributes for success 

• Working knowledge of data acquisition, data modelling, data products and data governance in complex organizations  

• Working knowledge in applying data analysis algorithms (statistics, machine learning, natural language processing, sentiment analysis, text mining, etc.) to analyse large amounts of data and deliver value creation points of view and recommendations 

• Experienc