Data Science Engineer, Analytics

Benefits

Parental leave

Not verified

Non-birth-parent leave

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Family-building benefits

• Fertility benefits: Not verified
• Adoption assistance: Not verified
• Surrogacy assistance: Not verified

Mental health support

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Relocation assistance

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Childcare support

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Learning budget

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Verification

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Salary

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Market context

U.S. role benchmark (BLS OEWS)

$116,543 U.S. median for this role

Projected growth (BLS Employment Projections)

+9.8% - Much faster than average

Matched to SOC 15-1252 - Software Engineering aggregate by role bucket.

Source: U.S. Bureau of Labor Statistics, OEWS, May 2024 and Employment Projections, 2024-2034.

Role

Role function

Engineering From the posting source checked Jun 20, 2026

Seniority

Mid From the posting source checked Jun 20, 2026

Work mode

Remote From the posting source checked Jun 20, 2026

In-office days

0 days From the posting source checked Jun 20, 2026

Schedule

Shift type

Not verified

Weekend work

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Application

Cover letter

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Assessment

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Deadline

Not stated

Where they hire

State eligibility is not yet verified.

About this role

Data Science Engineer, Analytics Remote This is a fully remote role within the United States. We're looking for a driven, entrepreneurial Data Science Engineer to join our team and help eliminate the financial complexity of healthcare. You'll join our Data Science Engineering team supporting analytics, partnering closely with Product, Engineering, and business stakeholders to help Turquoise grow and scale our impact by making better decisions with data. From defining product metrics and measuring customer engagement to enabling self-service analytics and evaluating business initiatives, you'll build the datasets, pipelines, dashboards, and analyses that transform data into actionable insights across the company. Responsibilities - Partner cross-functionally with Product, Engineering, and business stakeholders to define metrics, measure outcomes, and evaluate impact - Build and maintain data pipelines, data models, dashboards, and analytical infrastructure that support product, operational, and strategic decision-making - Conduct analyses to understand product adoption, customer engagement, business performance, and operational efficiency - Contribute to the development of analytics best practices, shared datasets, and company-wide metrics - Seek and act on feedback from internal stakeholders; iterate quickly with an eye toward value What you'll bring to the role - Bachelor's degree or equivalent experience. Non-traditional backgrounds welcome - 2+ years developing data models, pipelines, and end-to-end analytical solutions in Python and SQL. Comfortable with OOP and functional patterns, code organization beyond scripts, and debugging workflows - Experience with dataframe libraries (pandas, polars) - Experience with ETL/ELT workflows and orchestration (Airflow, dbt) - Comfort with cloud services (AWS S3, EC2,

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