Transaction Services - Data Analytics Senior Associate

As a Transaction Services Data Analytics Senior Associate at Riveron, you will provide crucial data-driven insights for complex transactions involving private equity and corporate clients. Your role analyzes extensive datasets to uncover trends and deliver actionable recommendations that guide clients through due diligence, post-deal performance, and exit strategies. You’ll translate complex data into clear insights for clients and internal teams, ensuring strategic decisions are well-informed. In this dynamic, fast-paced environment, you will stay ahead of industry trends and emerging technologies, enhancing our analytical approach, and delivering impactful results throughout the deal lifecycle. 

• Bachelor’s or master's in accounting, data science, data analytics, statistics, economics, or related field 
• CPA and/or audit experience preferred but not required 
• Minimum 2years of total relevant experience involving a combination of financial due diligence for transaction services and data analytics 
• Minimum 1 years of transaction experience focused on quality of earnings, net working capital, and cash flows 
• Minimum 1years of experience with one or a combination of the following: 
• Data Visualization Tools: Experience with D3.js, Tableau, PowerBI, Spotfire, or similar platforms. 
• Data Management: Proficiency in Hadoop, SQL, Alteryx, or comparable technologies. 
• Analytics Platforms: Knowledge of SAS, Azure, or related systems. 
• Statistical Software: Familiarity with SPSS, Minitab, or similar packages. 
• Programming Languages: Competence in Python, R, or other relevant languages. 
• You thrive in an ever-changing, dynamic work environment 
• You readily identify problems and instinctively look for solutions 
• You demonstrate analytical rigor and strong written and verbal communication skills  
• You have the ability and desire to travel as required based on client location 

• Analyze extensive datasets using data management technologies (e.g., Alteryx, Hadoop, SQL) to develop cleansed and organized datasets that will serve as input into M&A models, adjustments to EBITDA tables, net working capital analyses, or other key financial metrics. 
• Employ statistical software (e.g., SPSS, Minitab) and programming languages (e.g., Python, R) to perform in-depth analysis and identify trends, risks, and opportunities within transaction data. 
• Translate complex data findings into clear, strategic recommendations for due diligence and transaction models. 
• Utilize the application of analytics platforms (e.g., SAS, Azure) throughout the transaction lifecycle to make high-quality, data-driven decision-making and insights. 
• Stay updated with industry trends and emerging technologies to enhance our data analytics capabilities and support the delivery of impactful results for clients. 

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