Transaction Services - Data Analytics Senior Associate - riveron

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.

Who You Are

- 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 2 years of total relevant experience involving a combination of financial due diligence for transaction services and data analytics

- Minimum 1 year of transaction experience focused on quality of earnings, net working capital, and cash flows

- Minimum 1 year of experience with one or a combination of the following:

- Data Visualization Tools: Experience with D3.js http://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

What You'll Do

- 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.