\begin{tabular}{|l|l|l|l|l|l|}
\hline
\textbf{Profession} & \textbf{2021} & \textbf{2031} & \textbf{Change (in thousands)} & \textbf{Percent Change} & \textbf{Median Annual Wage} \\
\hline
Data entry keyers & 220.3 & 166.1 & -54.2 & -24.6\% & \[tex]$28,000 \\

\hline

Sewing machine operators & 161.4 & 119.7 & -41.7 & -25.8\% & \$[/tex]21,000 \\
\hline
Postal service mail sorters, processors, and processing machine operators & 129.6 & 91.0 & -38.6 & -29.8\% & \[tex]$53,000 \\

\hline

Farmworkers and laborers, crop, nursery, and greenhouse & 596.8 & 567.6 & -29.2 & -4.9\% & \$[/tex]18,670 \\
\hline
Word processors and typists & 104.4 & 78.2 & -26.2 & -25.1\% & \[tex]$35,270 \\

\hline

Postal service clerks & 66.9 & 45.7 & -21.3 & -31.8\% & \$[/tex]53,090 \\
\hline
\end{tabular}

According to the table, which profession is expected to lose the highest percentage of jobs?

A. Postal service mail carriers
B. Data entry keyers
C. Sewing machine operators
D. Postal service clerks

We start by identifying the percentage change in employment for each profession:

[tex]$$
\begin{array}{ll}
\text{Data entry keyers:} & -24.6\% \\
\text{Sewing machine operators:} & -25.8\% \\
\text{Postal service mail carriers:} & -29.8\% \\
\text{Postal service clerks:} & -31.8\%
\end{array}
$$[/tex]

A higher percentage loss means that the value is more negative. Comparing the values:

- Data entry keyers: [tex]$-24.6\%$[/tex]
- Sewing machine operators: [tex]$-25.8\%$[/tex]
- Postal service mail carriers: [tex]$-29.8\%$[/tex]
- Postal service clerks: [tex]$-31.8\%$[/tex]

The lowest (i.e., the most negative) percentage is [tex]$-31.8\%$[/tex].

Thus, the profession expected to lose the highest percentage of jobs is:

[tex]$$\textbf{Postal service clerks.}$$[/tex]