.tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] { padding-top: 20px;padding-bottom: 20px;border: 0px solid rgba( 36, 148, 81, 1 );grid-template-columns: minmax(0, 0.25fr) minmax(0, 0.25fr) minmax(0, 0.25fr) minmax(0, 0.25fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] > .tb-grid-column:nth-of-type(4n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] > .tb-grid-column:nth-of-type(4n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] > .tb-grid-column:nth-of-type(4n + 3) { grid-column: 3 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] > .tb-grid-column:nth-of-type(4n + 4) { grid-column: 4 } .tb-fields-and-text[data-toolset-blocks-fields-and-text="195e089501965b122c18569e34cf6b1b"] { padding-top: 10px; } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"] { grid-template-columns: minmax(0, 0.335fr) minmax(0, 0.665fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-fields-and-text[data-toolset-blocks-fields-and-text="2567880b60f0e64d3c543a6b43e3a746"] { padding-bottom: 20px; } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"] { grid-template-columns: minmax(0, 0.605fr) minmax(0, 0.395fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"] { grid-template-columns: minmax(0, 0.335fr) minmax(0, 0.665fr);grid-row-gap: 10px;grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] { grid-template-columns: minmax(0, 0.2fr) minmax(0, 0.16fr) minmax(0, 0.27333333333333fr) minmax(0, 0.18333333333333fr) minmax(0, 0.18333333333333fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] p { font-size: 20px;color: rgba( 125, 125, 125, 1 ); } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 3) { grid-column: 3 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 4) { grid-column: 4 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 5) { grid-column: 5 } .tb-fields-and-text[data-toolset-blocks-fields-and-text="25365352f0586ba74a4bc2109e88a762"] { font-size: 20px;color: rgba( 9, 40, 62, 1 ); } .tb-fields-and-text[data-toolset-blocks-fields-and-text="25365352f0586ba74a4bc2109e88a762"] p { font-size: 20px;color: rgba( 9, 40, 62, 1 ); } .tb-fields-and-text[data-toolset-blocks-fields-and-text="bc0deeaf4ddf2b4b635c19a219409f3f"] { color: rgba( 9, 40, 62, 1 ); } .tb-fields-and-text[data-toolset-blocks-fields-and-text="bc0deeaf4ddf2b4b635c19a219409f3f"] p { color: rgba( 9, 40, 62, 1 ); } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="93c5c97bc21707fc78a72f6bf21f104e"] { margin-top: -20px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="a779d194f82cce45870f9e78ba9f0889"] { font-size: 36px;margin-top: -10px;padding-top: -10px;border: 0px solid rgba( 218, 230, 242, 1 ); } .tb-fields-and-text[data-toolset-blocks-fields-and-text="a779d194f82cce45870f9e78ba9f0889"] p { font-size: 36px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="63c2dcb8092f841fa31d94d4621fa90a"] { padding-bottom: 15px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="92defc37c58bc95f0959e21855a33c6c"] { margin-bottom: 15px;padding-top: 5px;padding-bottom: 5px;border-top: 1px solid rgba( 218, 230, 242, 1 );border-bottom: 1px solid rgba( 218, 230, 242, 1 );box-shadow: 0 5px 10px -9px rgba( 146, 167, 191, 1 ); } .tb-fields-and-text[data-toolset-blocks-fields-and-text="592a2fa3d8dfe9091f29e10147202769"] { margin-top: -60px; } @media only screen and (max-width: 781px) { .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] { grid-template-columns: minmax(0, 0.3333fr) minmax(0, 0.3333fr) minmax(0, 0.3333fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] > .tb-grid-column:nth-of-type(3n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] > .tb-grid-column:nth-of-type(3n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] > .tb-grid-column:nth-of-type(3n + 3) { grid-column: 3 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"] { grid-template-columns: minmax(0, 0.5fr) minmax(0, 0.5fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"] > .tb-grid-column:nth-of-type(2n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"] > .tb-grid-column:nth-of-type(2n + 2) { grid-column: 2 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] { grid-template-columns: minmax(0, 0.3333fr) minmax(0, 0.3333fr) minmax(0, 0.3333fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(3n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(3n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(3n + 3) { grid-column: 3 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; }  } @media only screen and (max-width: 599px) { .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="a800c7f7983f56e1f9f3a3d15a25529f"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="f0e31d660193acaf11948a2c3673a7b7"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"] { grid-template-columns: minmax(0, 1fr);grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="b4ba35a082eaf5f3ddf71774e7effd6f"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"] { grid-template-columns: minmax(0, 1fr);grid-row-gap: 10px;grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="924898f5c635c41dd5487cba6d83d569"]  > .tb-grid-column:nth-of-type(1n+1) { grid-column: 1 } .tb-grid,.tb-grid>.block-editor-inner-blocks>.block-editor-block-list__layout{display:grid;grid-row-gap:25px;grid-column-gap:25px}.tb-grid-item{background:#d38a03;padding:30px}.tb-grid-column{flex-wrap:wrap}.tb-grid-column>*{width:100%}.tb-grid-column.tb-grid-align-top{width:100%;display:flex;align-content:flex-start}.tb-grid-column.tb-grid-align-center{width:100%;display:flex;align-content:center}.tb-grid-column.tb-grid-align-bottom{width:100%;display:flex;align-content:flex-end} .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] { grid-template-columns: minmax(0, 0.2fr) minmax(0, 0.2fr) minmax(0, 0.2fr) minmax(0, 0.2fr) minmax(0, 0.2fr);grid-column-gap: 0px;grid-auto-flow: row } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] p { font-size: 13px; } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 1) { grid-column: 1 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 2) { grid-column: 2 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 3) { grid-column: 3 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 4) { grid-column: 4 } .wp-block-toolset-blocks-grid.tb-grid[data-toolset-blocks-grid="1613c21c9a17c2fd14665037dce62cfa"] > .tb-grid-column:nth-of-type(5n + 5) { grid-column: 5 } .wp-block-toolset-blocks-grid-column.tb-grid-column[data-toolset-blocks-grid-column="3034fbe886c11054e95b46b09d3e4112"] { display: flex; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="92defc37c58bc95f0959e21855a33c6c"] { padding-top: -20px; } .tb-fields-and-text[data-toolset-blocks-fields-and-text="592a2fa3d8dfe9091f29e10147202769"] { padding-top: -20px;margin-top: -20px; }  } 

Statistical Technician Salary

SALARY JOB OUTLOOK AUTOMATION RISK

Average Statistical Technician Base Salary in the United States

Average Base Salary

$54,041 Per Year

Salary Range: $34,441 to $81,528

$34,441

10%

$38,685

25%

$ 54,041

AVERAGE

$63,614

75%

$81,528

90%

How Much Does a Statistical Technician Make Per Year in the United States?

The national average salary for a Statistical Technician is $54,041 per year in the United States. It can vary depending on the employer and the skills required for that position, but generally, it will be about $54,041 or more annually for a gross salary. Taxes impact salaries, so to get the net salary we’ve crunched the data and gotten the tax information on what the take-home pay would be after the effective income tax rates.

Jobs That are Similar to a Statistical Technician

Technology Used

Microsoft Excel – Spreadsheet software

Microsoft PowerPoint – Presentation software

Database software – Data base user interface and query software

The MathWorks MATLAB – Analytical or scientific software

Python – Object or component oriented development software

Microsoft Visual Basic – Development environment software

Tableau – Business intelligence and data analysis software

Bentley MicroStation – Computer aided design CAD software

Knowledge and Expertise

Mathematics

Computers and Electronics

Customer and Personal Service

Education and Training

Administrative

Administration and Management

Soft Skills

Mathematics

Reading Comprehension

Critical Thinking

Active Learning

Complex Problem Solving

Writing

What is the salary range of a Statistical Technician?

Statistical Technician salaries vary depending on the company you work for, your experience level, industry, education, and years of experience. The average annual salary is around $54,041 but a Statistical Technician can earn a base salary anywhere from $34,441 to $81,528 per year with some companies paying more than others.

Pay ranges on average for a Statistical Technician job title only vary a good amount, which may mean that there are many opportunities to earn more income in the future regardless of the employers or your location, industry, and experience.

A salary range that varies also means there is ability to move up within the company, as there may be as many opportunities for advancement or to change your job title. This opportunity for advancement can help with can increase their job satisfaction and motivation.

What are the Highest Salaries for a Statistical Technician?

The highest Statistical Technician salaries in the top 10% earn more than $81,528 per year. The salary range for the top 75% – 90% is between and $63,614 and $81,528 annually.

This salary data and salary estimates come from our Average Pay’s salary database of carefully collected and detailed information about pay across many industries and categories, along with different types of labor data.

What are the Lowest Salaries for a Statistical Technician?

The lowest Statistical Technician salaries are in the bottom 10% of earners who make less than $34,441 per year. The salary range for the lowest 10% – 25% is between $34,441 and $38,685 annually.

What is a Good Salary for a Statistical Technician?

If we only look at the data for Statistical Technician salaries and we don’t compare it to any other jobs, a good salary for a Statistical Technician job would be over $54,041 per year. This is the average salary for this position in the United States. An excellent pay for a Statistical Technician would be anything over the top 75%, which is $63,614 annually.

How Can I Increase My Salary as a Statistical Technician?

There are a few ways you can increase your average salary for a profession as a Statistical Technician. One way is to get promoted to a higher level and take on more duties within your employer. Another way is to gain more experience and skills in your career. You can also try negotiating higher compensation next performance review, when you are up for renewal or starting a new contract with a business.

Finally, you can look for a new job at a different employer that pays more. One thing not to overlook is companies often give their employees incentives and benefits outside of salaries. The total compensation, like healthcare, paid vacation days, 401k matches, bonuses, overtime, professional development, a career path in the company, and other benefits, need to be considered, which can add up to a lot more money than just a salary increase.

What are the Top Paying Industries for a Statistical Technician?

The top paying industries for a Statistical Technician job vary depending on the position’s specific responsibilities, employers, and qualifications. However, some common reported high-paying industries for include the following:

Professional, Scientific, and Technical Services
Professional, Scientific, and Technical Services
Federal, State, and Local Government
Colleges, Universities, and Professional Schools
Finance and Insurance
Finance and Insurance

Related Jobs For a Statistical Technician

Actuarial Technician

Data Technician

Statistical Assistant

Statistical Research Assistant

Statistical Analyst

Statistical Assistants

Statistical Clerk

Survey Data Technician

Does a Statistical Technician Have a Good Quality of Life?

Based on an average 2-bedroom apartment rental price, a Statistical Technician would pay 15.63% of their monthly take-home pay towards rent. That’s $1,310 per month or $15,720 yearly for a two-bedroom apartment.

The rent is less than 30% of the monthly take-home pay for an Statistical Technician, which can helps lessen a financial burden and impact their quality of life.

This is because a high rent-to-income ratio would leave less money each month for other expenses, such as food, transportation, recreation, and activities. It can lead to financial stress, impacting overall job satisfaction and motivation.

Considering the cost of living in a city when considering whether to accept a job offer is essential. If the cost of living is too high, it might not be worth it, even if the salary is good.

Does a Statistical Technician make good money?

In general, a Statistical Technician can make a good salary. The national average salary is $52,632 annually which is less than the average Statistical Technician salary, meaning most earn a livable wage. According to data and labor statistics from the Bureau of Labor Statistics, the average Statistical Technician pay is above the median salary.

However, salaries can vary depending on the company you work for, what you are responsible for, education, college degree, work experience, job market, and your experience level. The highest-paid can earn upwards of 81,528 per year, while the lowest-paid income is less than 34,441 annually.

If you want to maximize your earnings as a Statistical Technician, take on more responsibility, and gain more experience in related skills. Also, build interpersonal skills and strong leadership skills, get a certification in your field and then negotiate for a higher salary next performance review, when you are up for renewal or starting a new contract with a business.

The best thing you can do is develop yourself and gain knowledge. Many courses, additional training, and professional development opportunities in your area can help increase your skills and development in your job or related field.

You can also get your resume reviewed and look for a new employer that will hire and pay more or look for a career change that is hiring and may interest you more.

Salaries are also relative to the cost of living in different parts of the country. For example, the compensation for a Statistical Technician will need to be higher if it is in or closer to larger cities like New York City or some states like California. The increase in pay in these areas is because of the higher than average cost of living and more interested applicants for employment versus someone living in a small town. With the cost of housing increasing and medical care premium costs, it is essential to ensure you are getting paid what you are worth.

How do I know I’m being paid fairly as a Statistical Technician?

The easiest way is to see how close your current salary is to the average pay for your position in your state and city. If your income is below the estimated average wage in your area, you can try to negotiate for a raise.

You can use our research and tools to discover the average salary for a Statistical Technician in your city or region to see if you are being compensated fairly. You may also compare your income to similar jobs and careers to determine whether you are underpaid or overpaid. Lastly, you can set up job alerts to see how the job market trends.

A few other ways you can research whether you’re being paid fairly as a Statistical Technician is to do a job search to look at job postings for similar positions and see the estimate for the listed salary range. You can also talk to people in your network who have similar jobs and ask them what they earn. Finally, you can try negotiating a higher pay when you are up for renewal, having a performance evaluation, or starting a new contract.

What Factors Determine the Salary of a Statistical Technician?

The money a Statistical Technician can make each year greatly depends on a few components that determine an average base salary.

The company you work for is one of the main factors that affect how much a Statistical Technician earns.

The compensation will also depend on the location, as some states and cities have a higher cost of living than others. Other factors that affect compensation are the number of hours worked, company size, job type, level of experience in your career, and location.