To solve the given optimization problem, we first need to translate the natural language description into a mathematical formulation. The objective function is to maximize:

7.08 * hours_worked_by_Mary + 2.43 * hours_worked_by_George + 4.45 * hours_worked_by_Bill

Subject to several constraints based on computer competence ratings, work quality ratings, paperwork competence ratings, and organization scores.

Let's denote:
- \(M\) as the hours worked by Mary,
- \(G\) as the hours worked by George,
- \(B\) as the hours worked by Bill.

Given data:
- Computer competence ratings: Mary = 15, George = 4, Bill = 12
- Work quality ratings: Mary = 2, George = 6, Bill = 10
- Paperwork competence ratings: Mary = 7, George = 12, Bill = 6
- Organization scores: Mary = 6, George = 8, Bill = 4

Constraints:
1. \(15M + 12B \geq 38\)
2. \(15M + 4G + 12B \geq 53\)
3. \(6M + 4B \geq 28\)
4. \(6M + 8G + 4B \geq 29\)
5. \(4G + 12B \leq 156\)
6. \(15M + 4G + 12B \leq 156\)
7. \(2M + 10B \leq 66\)
8. \(2M + 6G + 10B \leq 92\)
9. \(7M + 6B \leq 100\)
10. \(7M + 12G + 6B \leq 100\)
11. \(8G + 4B \leq 33\)
12. \(6M + 8G + 4B \leq 33\)

Since the problem allows for non-integer solutions for all variables, we can model this as a linear programming problem.

```python
from gurobipy import *

# Create a new model
m = Model("Optimization_Problem")

# Define variables
M = m.addVar(lb=0, name="hours_worked_by_Mary")
G = m.addVar(lb=0, name="hours_worked_by_George")
B = m.addVar(lb=0, name="hours_worked_by_Bill")

# Objective function: Maximize
m.setObjective(7.08*M + 2.43*G + 4.45*B, GRB.MAXIMIZE)

# Constraints
m.addConstr(15*M + 12*B >= 38, "ComputerCompetence_MaryBill")
m.addConstr(15*M + 4*G + 12*B >= 53, "ComputerCompetence_All")
m.addConstr(6*M + 4*B >= 28, "OrganizationScore_MaryBill")
m.addConstr(6*M + 8*G + 4*B >= 29, "OrganizationScore_All")
m.addConstr(4*G + 12*B <= 156, "ComputerCompetence_GeorgeBill_Max")
m.addConstr(15*M + 4*G + 12*B <= 156, "ComputerCompetence_All_Max")
m.addConstr(2*M + 10*B <= 66, "WorkQuality_MaryBill_Max")
m.addConstr(2*M + 6*G + 10*B <= 92, "WorkQuality_All_Max")
m.addConstr(7*M + 6*B <= 100, "PaperworkCompetence_MaryBill_Max")
m.addConstr(7*M + 12*G + 6*B <= 100, "PaperworkCompetence_All_Max")
m.addConstr(8*G + 4*B <= 33, "OrganizationScore_GeorgeBill_Max")
m.addConstr(6*M + 8*G + 4*B <= 33, "OrganizationScore_All_Max")

# Optimize model
m.optimize()

# Print solution
for v in m.getVars():
    print(f"{v.VarName}: {v.X}")

print("Obj:", m.ObjVal)
```