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# Lead Data Scientist

- **Company:** REMOTE HAND
- **Location:** United States (Remote available)
- **Experience:** Expert
- **Salary:** $156,500.0 - $215,300.0
- **Contract:** Permanent contract
- **Skills:** Business Analytics Applications, Machine Learning, SQL Databases, Data Strategy, Information Technology, Data Analytics
- **Published:** August 24, 2026
- **Apply:** https://arc.dev/remote-jobs/j/redirect/pelbcz061f

## About the Role

* Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related field.

 * Minimum 8 years of professional experience in data and analytics.

 * At least 5 years of experience using SQL.

 * Minimum 4 years of project leadership experience.

 * Strong expertise in mathematics, statistics, predictive modeling, machine learning, and business analysis.

 * Experience solving moderately to highly complex analytical and business problems.

 * Ability to independently exercise sound judgment and work effectively with minimal supervision.

 * Strong communication and stakeholder management skills.

## Description

The Lead Data Scientist develops advanced analytics solutions that influence business strategy and promote policy adherence. This role is responsible for designing metrics, models, and valuation frameworks that measure compliance and financial impact. By partnering with data, compliance, policy, and business teams, the position helps operationalize analytics solutions, improve decision-making, and shape the organization's approach to policy governance and data-driven strategy.

Responsibilities

 * Develop, maintain, and collect structured and unstructured datasets for analysis and reporting.

 * Create reports, projections, analytical models, and presentations to support business strategy.

 * Advise executives on functional strategies related to policy adherence and compliance.

 * Develop strategies for innovative analytics solutions that improve compliance and decision-making.

 * Research, design, and implement policy adherence metrics using advanced data modeling techniques.

 * Design valuation models to measure savings generated through compliance improvements.

 * Partner with national teams to support the adoption and operational use of analytics metrics.

 * Manage relationships with data owners, compliance teams, policy teams, and business stakeholders.

 * Influence analytics priorities and roadmap decisions for scalable solution implementation.


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