פרוייקטים לפרילנסרים בתחום סטטיסטיקה

Liquidity Model – Statistical Validation Analyst
Objective
Design and implement statistical tests to validate a banking liquidity / ALM model.
Focus is on rigor, reproducibility, and defensibility - not research or theory.
The analyst will work under a statistics manager, so deep theoretical expertise is not required. Strong applied statistical competence is required.

Required Background
Mandatory
● Solid understanding of financial accounting (balance sheet logic, cash flows)
● Strong applied statistics
○ Hypothesis testing
○ Distribution testing
○ Backtesting
○ Stability analysis
○ Sensitivity analysis
○ Time-series basics

● Comfortable implementing statistically sound tests with high accuracy
● SQL + Python (pandas / scipy / statsmodels) or R

Advantage
● Exposure to ALM / liquidity risk / treasury

Scope (≈50 Hours)
1. Review liquidity model assumptions and data
2. Design appropriate statistical validation tests
3. Implement tests in Pyspark/SQL
4. Document methodology and findings
5. Highlight weaknesses and improvement areas

Expected Output
● Clear, defensible statistical framework
● Reproducible code
● Well-documented assumptions
● Practical recommendations
The role requires applied statistical competence and financial literacy — strategic oversight is provided by a statistical manager.