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# Sr. Data Scientist

- **Company:** Slickdeals, LLC
- **Location:** San Jose, CA, United States
- **Experience:** Expert
- **Salary:** $145,000.0 - $175,000.0
- **Contract:** Permanent contract
- **Skills:** A/B Testing, Big Data, Data Visualization, Python (Programming Language), Machine Learning, SQL Databases, Information Technology
- **Published:** July 18, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=45b252c58bf4076f

## About the Role

* Advanced degree (MS or PhD) in Statistics, Economics, Computer Science, Engineering, Sciences, or another quantitative field.
 * 5+ years of experience in a Data Scientist role.
 * Strong track record designing, executing, and interpreting A/B tests using causal inference methodologies.
 * Proficiency in SQL and Python or R, with experience working with large scale datasets and data visualization tools.
 * Proven experience translating data into actionable recommendations for executives and cross functional teams.
 * Strong analytical mindset with the ability to navigate ambiguity and uncover meaningful insights from complex business problems.
 * Excellent communication and interpersonal skills with the ability to collaborate effectively in fast paced, cross functional environments., Candidates must be eligible to work in the United States.

## Description

Slickdeals is seeking a Senior Data Scientist to help shape how we grow by partnering with Product, Design, Engineering, Finance, and Marketing to deepen our quantitative understanding of what drives user growth. In this role, you'll combine data science, statistics, and causal inference to develop the frameworks and insights that inform product decisions and shape our growth strategy. As a trusted cross functional partner, you'll turn complex business questions into actionable insights that help us build products our users love.

What You'll Do:

 * Partner with Product, Design, Engineering, Finance, and Marketing to inform product development and growth strategy through data driven insights.
 * Identify new opportunities, define success metrics, quantify business challenges, and turn open ended questions into structured, high impact analytics projects.
 * Build scalable measurement frameworks, including lifetime value (LTV) and retention models, to evaluate growth initiatives and support data driven decision making.
 * Design, execute, and interpret A/B tests to evaluate product changes and validate hypotheses using causal inference, machine learning methodologies, and experimentation best practices.
 * Develop dashboards and reporting that make key metrics and insights accessible and actionable across the organization.
 * Translate complex analyses into clear narratives, recommendations, and data stories that influence both technical and non technical stakeholders.
 * Collaborate across teams to strengthen the data foundation that supports user growth and experimentation at scale.


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