Investment Data Analyst

Lendo; Riyadh; On-site; SAR 60,000 - 80,000; Full time

Job summary

A fast-growing FinTech company in Saudi Arabia is seeking an Investment Data Analyst to support strategic investment decisions. The role involves data aggregation, analysis, and visualization to optimize capital performance and track key investment metrics. Ideal candidates will have experience in fintech, strong analytical skills, and proficiency in Tableau and SQL.

Qualifications

• 2–5 years of experience as a Data Analyst in fintech or financial services.
• Proven experience with Tableau and Power BI for dashboard creation.

Responsibilities

• Collect and consolidate data from various sources for investment analysis.
• Design and maintain dashboards to track investor performance metrics.
• Analyze financial data to identify trends and risks in investment portfolios.

Skills

Analytical Mindset

Communication

Problem Solving

Education

Bachelor’s degree in Finance

Master’s degree or CFA certification

Tools

Tableau

Power BI

SQL

Excel

Python

Job description

At Lendo, we are a fast-growing FinTech company on a mission to revolutionize the financial landscape in Saudi Arabia. Through our innovative digital lending platform, we empower SMEs by providing fast, secure, and transparent access to capital - fueling economic growth and aligning with Vision 2030.

As we continue to expand, we’re looking for a skilled and proactive Investment Data Analyst to join our Investment and Capital team. This pivotal role will focus on aggregating, analyzing, and visualizing data to support strategic investment decisions, optimize capital performance, and track key metrics such as default rates and collection efficiency. You’ll work cross-functionally to build dashboards and reports using tools like Tableau, playing a critical role in turning raw data into actionable insights for both internal stakeholders and external investors.

Key Responsibilities:

• Data Aggregation and Management:

  • Collect and consolidate data from internal systems, financial databases, and external sources (e.g., market trends, investor portfolios, loan performance).

  • Ensure data accuracy, integrity, and consistency by implementing quality checks and cleaning processes.

  • Maintain and update databases related to investments, capital allocation, and collections.

• Reporting and Visualization:

  • Design, develop, and maintain interactive dashboards and reports using Tableau and other platforms (e.g., Power BI, Excel, or Python-based tools) to track:

    • Investor performance metrics (ROI, portfolio growth, risk exposure).

    • Investment opportunities in Saudi Arabia’s dynamic sectors (e.g., real estate, infrastructure, technology).

    • Default rates and trends in loan repayments.

    • Efficiency of the collection process and recovery rates.

  • Present complex data in clear, visually appealing formats tailored to stakeholders, including investment managers, executives, and investors.

• Investment and Performance Analysis:

  • Analyze financial data to identify trends, correlations, and risks in investment portfolios.

  • Evaluate potential investment opportunities by assessing market conditions, sector performance, and macroeconomic factors (e.g., Saudi Arabia’s infrastructure projects, green energy initiatives/ESG).

  • Provide insights on investment performance, delinquency patterns, and collection strategies to optimize capital recovery.

• Collaboration and Communication:

  • Work closely with investor relations managers, relationship managers, credit team, and the operations and collections team to align data insights with business objectives.

  • Communicate findings and recommendations effectively through presentations, reports, and meetings.

  • Collaborate with IT, business intelligence and data engineering teams to streamline data pipelines and integrate new data sources.

• Process Optimization:

  • Identify opportunities to automate data collection, reporting, and analysis processes to improve efficiency.

  • Support the development of predictive models to forecast investor performance, default risks, or collection outcomes (using Python, R, or similar tools).

• Compliance and Governance:

  • Ensure data handling complies with Saudi Arabia’s financial regulations, data privacy laws, and Lendo’s internal policies.

  • Support audits and regulatory reporting by providing accurate and timely data.

Qualifications:

• Education:

  • Bachelor’s degree in Finance, Economics, Statistics, Data Science, Computer Science, or a related field. A master’s degree or CFA certification is a plus.

• Experience:

  • 2–5 years of experience as a Data Analyst, preferably in fintech, investment banking, or financial services.

  • Proven experience with Tableau and Power BI for dashboard creation and data visualization.

  • Familiarity with investment analysis, capital markets, or loan performance metrics (e.g., default rates, collections).

• Technical Skills:

  • Proficiency in Tableau and other BI tools (Power BI, QlikView).

  • Advanced Excel skills (pivot tables, VLOOKUP, macros).

  • Experience with SQL for querying and managing large datasets.

  • Knowledge of Python or R for data analysis and modeling is preferred.

  • Familiarity with financial databases (e.g., Bloomberg, Refinitiv) is a plus.

• Soft Skills:

  • Strong analytical mindset with attention to detail and problem-solving abilities.

  • Excellent communication and presentation skills to convey insights to non-technical stakeholders.

  • Ability to work under pressure and manage multiple priorities in a fast-paced environment.

• Knowledge:

  • Understanding of Saudi Arabia’s investment landscape, including Vision 2030 initiatives and sectors like infrastructure, real estate, and renewable energy.

  • Familiarity with fintech lending processes, default rate analysis, and collection strategies.

• Preferred Qualifications:

  • Experience working in Saudi Arabia or the GCC region, with knowledge of local financial regulations (e.g., SAMA, CMA).

  • Arabic language proficiency (written and spoken) is a strong advantage.

  • Exposure to machine learning or predictive analytics for financial forecasting.