- Company Name
- Aria Partners
- Job Title
- Portfolio Data Analyst - Private Equity
- Job Description
-
**Job Title:** Portfolio Data Analyst – Private Equity
**Role Summary:**
Lead the development and enhancement of data, analytics, and AI capabilities across investment, portfolio, impact, investor relations, and finance functions. Own the integration of multiple data sources to create actionable insights that support fast, evidence‑based decision making within a private equity environment.
**Expectations:**
- Build a scalable analytics platform (SQL Server, Databricks, Power BI) to deliver high‑quality, real‑time reporting on portfolio performance, fund performance, and pipeline investment.
- Drive innovation through AI tooling and advanced analytical techniques.
- Influence non‑technical stakeholders and collaborate cross‑functionally to align analytics objectives with business goals.
**Key Responsibilities:**
- Design, develop, and maintain Power BI dashboards and reports for investment, finance, and investor relations teams.
- Extract, clean, model, and load data using SQL and Python; ensure data integrity and performance of the SQL Server and Databricks environments.
- Connect disparate systems and datasets, creating a unified data pipeline that supports portfolio and fund analytics.
- Evaluate and select AI tools to enhance data analysis, model development, and decision support.
- Collaborate with investment and finance teams to understand analytical needs, translate them into technical solutions, and provide guidance on data-driven decision making.
- Present insights and findings to senior stakeholders, translating complex data into actionable business recommendations.
- Continuously improve data governance, documentation, and automated testing processes.
**Required Skills:**
- 3‑5 years of portfolio analytics, data analytics, or related experience (consulting, private equity, or financial services).
- Advanced Power BI development and reporting; proficiency in creating dynamic, interactive dashboards.
- Strong SQL skills (T‑SQL, database design, query optimization).
- Proficient in Python (pandas, NumPy, scikit‑learn, or similar libraries for data manipulation and modeling).
- Experience with cloud data platforms (Databricks, Azure, or similar).
- Knowledge of AI/ML concepts and familiarity with AI tooling.
- Excellent communication and stakeholder‑management abilities; confidence presenting to executive audiences.
- Commercial mindset with a clear focus on investment outcomes.
**Required Education & Certifications:**
- Bachelor’s degree (or equivalent) in Finance, Economics, Data Science, Computer Science, Statistics, or a related quantitative field.
- Relevant certifications (e.g., Microsoft Power BI, Microsoft Certified: Azure Data Engineer Associate, or equivalent SQL/Databricks credentials) are advantageous.