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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Data Scientist - **Company:** Fanatics Inc - **Location:** Los Angeles, CA, United States - **Experience:** Starter - **Salary:** $122,040.0 - $152,550.0 - **Contract:** Permanent contract - **Skills:** A/B Testing, Airflow, Data Analysis, Big Data, BigQuery, Data Validation, Decision Support Systems, Github, Google Analytics, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Regression Analysis, Mixpanel, Cloud Services, Standard Sql, SQL Databases, Tableau (Software), Snowflake, Scikit Learn, Information Technology, Data Analytics, Looker Analytics, Data Pipelines - **Published:** July 2, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=d35d56bbb4c469b0 ## About the Role * Bachelor's degree in Statistics, Mathematics, Computer Science, Data Science, or another quantitative field, or equivalent practical experience. * 1-3 years of experience in data science, analytics, or a related quantitative role. * Working knowledge of SQL and experience querying large datasets. * Proficiency in Python or R for data analysis. * Foundational understanding of statistics, hypothesis testing, regression analysis, and experimental design. * Familiarity with machine learning concepts and common libraries such as scikit-learn. * Strong analytical thinking, curiosity, and willingness to learn new technologies. * Excellent communication and collaboration skills., * Master's degree in a quantitative discipline. * Experience with business intelligence tools such as Sigma, Looker, or Tableau. * Exposure to cloud data platforms including Snowflake or BigQuery. * Coursework or practical experience with machine learning, forecasting, or experimentation. * Experience working in consumer technology, e-commerce, marketplaces, or digital products. * Familiarity with behavioral analytics platforms such as Mixpanel, Amplitude, or Google Analytics. ## Description As a Data Scientist, you will support the development of analytical models, experimentation, and reporting that help improve our products and inform business decisions. Working closely with senior data scientists, product managers, engineers, and analysts, you will apply statistical methods and machine learning techniques to analyze data, uncover insights, and contribute to data-driven product improvements. This role is ideal for someone early in their data science career who is eager to expand their technical skills while gaining experience in a fast-paced, product-focused environment. What You'll Do * Partner with Product, Engineering, and Analytics teams to understand business questions and support data-driven decision making. * Build, validate, and maintain analytical models and data pipelines under the guidance of senior team members. * Perform statistical analyses and exploratory data analysis to identify trends, patterns, and opportunities. * Support A/B testing initiatives by assisting with experiment design, data validation, statistical analysis, and communicating results. * Develop dashboards and reports using tools such as Sigma or Looker to help stakeholders monitor product performance and key business metrics. * Write efficient SQL queries and work with cloud-based data warehouses such as Snowflake or BigQuery to prepare and analyze data. * Use Python or R to automate analyses and develop reproducible analytical workflows. * Leverage AI-assisted development tools (such as Claude or OpenAI) and engineering platforms (GitHub, Airflow) to improve productivity and collaboration. * Collaborate with senior data scientists to improve existing models and analytical processes while continuing to build technical expertise. * Clearly communicate analytical findings and recommendations to technical and non-technical stakeholders. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works) - [Innovating Developer Tools with AI: Insights from GitHub Next](https://www.wearedevelopers.com/videos/1268-innovating-developer-tools-with-ai-insights-from-github-next) - [PySpark - Combining Machine Learning & Big Data](https://www.wearedevelopers.com/videos/44-pyspark-combining-machine-learning-big-data) - [Enjoying SQL data pipelines with dbt](https://www.wearedevelopers.com/videos/823-enjoying-sql-data-pipelines-with-dbt) ## Related Articles - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers) - [Top Big Data Technologies That You Need to Know](https://www.wearedevelopers.com/magazine/108-top-big-data-technologies-that-you-need-to-know) - [Making Data Warehouses Fast: A Developer’s Story](https://www.wearedevelopers.com/magazine/107-making-data-warehouses-fast-a-developer-s-story) - [Data Analyst Salary in the UK](https://www.wearedevelopers.com/magazine/278-data-analyst-salary-in-the-uk) - [Data Engineer Salary UK](https://www.wearedevelopers.com/magazine/253-data-engineer-salary-uk) - [How Much FAANG Companies Actually Pay Software Engineers in 2025](https://www.wearedevelopers.com/magazine/230-how-much-faang-companies-actually-pay-software-engineers-in-2025)