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Software Engineer (Data Science)

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March 29, 2024 Updated April 14, 2025 16 minute read

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Software Engineer (Data Science): A Comprehensive Career Guide

A Software Engineer specializing in Data Science occupies a critical intersection between software development and data analysis. This role involves designing, building, and maintaining the software systems and infrastructure that enable data scientists to develop, deploy, and monitor machine learning models and data analytics applications effectively. They are the engineers who ensure that data-driven insights can be reliably delivered at scale within production environments.

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Salaries for Software Engineer (Data Science)

City

25th Percentile

50th Percentile

75th Percentile

Median

New York

$172,000

$220,000

$247,000

$220,000

San Francisco

$158,000

$194,000

$246,000

$194,000

Seattle

$125,000

$150,000

$187,000

$150,000

See all salaries

City

25th Percentile

50th Percentile

75th Percentile

Median

New York

$172,000

$220,000

$247,000

$220,000

San Francisco

$158,000

$194,000

$246,000

$194,000

Seattle

$125,000

$150,000

$187,000

$150,000

Austin

$145,000

$213,000

$279,000

$213,000

Toronto

$114,400

$151,000

$182,000

$151,000

London

£66,000

£90,000

£122,000

£90,000

Paris

€52,000

€62,000

€85,000

€62,000

Berlin

€55,000

€65,000

€78,000

€65,000

Tel Aviv

₪395,000

₪470,000

₪597,000

₪470,000

Singapore

S$94,000

S$125,000

S$171,000

S$125,000

Beijing

¥327,000

¥538,000

¥825,000

¥538,000

Shanghai

¥255,000

¥365,000

¥505,000

¥365,000

Shenzhen

¥313,000

¥505,000

¥653,000

¥505,000

Bengalaru

₹2,210,000

₹3,278,000

₹5,102,000

₹3,278,000

Delhi

₹1,190,000

₹2,200,000

₹3,650,000

₹2,200,000

Bars indicate relevance. All salaries presented are estimates. Completion of this course does not guarantee or imply job placement or career outcomes.

Path to Software Engineer (Data Science)

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We've curated one courses to help you on your path to Software Engineer (Data Science). Use these to develop your skills, build background knowledge, and put what you learn to practice.

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Introduction to Data Analysis with Pandas and NumPy

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