Senior Data Scientist, Product Analytics
New
B
BOLDProduct analytics
This position is 100% remote, work from home. BOLD can hire full-time residents of the following U.S. States & Territories: Arizona, California, Colorado, Connecticut, District of Columbia (Washington D.C) Florida, Georgia, Illinois, Indiana, Kentucky, Maine, Maryland, Massachusetts, New Hampshire, New Jersey, New York, North Carolina, Ohio, Pennsylvania, Puerto Rico, South Carolina, Tennessee, Texas, Utah, Virginia, Washington, and Wisconsin.Full-TimeSenior
SalaryStarting pay range $145,000 — $170,000 USD
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Job Details
- Experience
- 7+ years’ experience performing quantitative data analysis, preferably for an internet or technology company.
- Required Skills
- PythonSQLGoogle AnalyticsTableauA/B testingLookerR
Requirements
- Have 7+ years of experience performing quantitative data analysis; experience at an internet or technology company is preferred.
- Write complex SQL queries to drive business decisions.
- Demonstrate a robust understanding of statistics and explain statistical concepts to non-technical audiences.
- Hold a bachelor’s or master’s degree in Math, Engineering, Statistics, or another quantitative field, with a track record of academic excellence.
- Demonstrate the ability to handle multiple projects, meet deadlines in a fast-paced environment, and make a meaningful business impact.
- Have excellent communication skills.
- Be proficient with Python/R.
- Be proficient with BI tools such as Tableau, Looker, or equivalent.
- Have experience with Google Analytics, Mixpanel, or other front-end analytical platforms.
- Experience using AI technologies such as Claude, GPT, or Gemini is a plus.
Responsibilities
- Conduct in-depth analysis to uncover opportunities for improving products.
- Build advanced models and analytics tools to improve product insights and recommendations.
- Develop data-driven insights and recommendations and communicate them to business stakeholders.
- Analyze A/B tests to drive user conversion and engagement.
- Develop dashboards to inform business decisions, emphasizing automation and scalability.
- Collaborate with Engineering to advance data infrastructure and governance.
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