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 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
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.
- 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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Last updated on Aug 12, 2024