Junior Data Scientist A/B testing

Key Responsibilities

Experiment Strategy & Design • Develop clear experimentation hypotheses aligned with business goals. • Define primary and secondary success metrics for tests. • Calculate sample sizes, statistical power, and estimated test duration to ensure reliable outcomes.

Test Execution • Manage experiment setup, including user segmentation and randomization strategies. • Work with engineering teams to validate tracking implementation and maintain data quality and integrity. • Monitor experiment performance throughout the testing lifecycle.

Statistical Analysis • Analyze experiment results using statistical techniques such as hypothesis testing, p-values, and confidence intervals. • Interpret findings to determine statistical and practical significance. • Perform deeper segment-level analysis to uncover insights across different user groups.

Reporting & Optimization • Present insights and recommendations to technical and non-technical stakeholders in a clear, actionable manner. • Maintain documentation of experiment outcomes, learnings, and optimization opportunities. • Contribute to and manage the experimentation roadmap for continuous website improvement.

Required Skills & Qualifications

Statistical & Analytical Skills • Strong understanding of experimental design, probability, and hypothesis testing. • Familiarity with Frequentist and Bayesian experimentation methodologies is preferred.

Technical Skills • Proficiency in SQL for data extraction and analysis. • Hands-on experience with Python or R for statistical modeling and experiment analysis.

Experimentation & Analytics Tools • Experience using experimentation platforms such as Optimizely, VWO, or LaunchDarkly. • Knowledge of web analytics tools such as Google Analytics 4.

Data Visualization • Ability to create dashboards and performance reports using tools like Tableau, Power BI, or Looker.

Communication & Collaboration • Strong problem-solving and critical-thinking abilities. • Excellent communication skills with the ability to explain complex findings and business impact to non-technical audiences.

Education & Experience • Bachelor’s degree in a quantitative discipline such as Statistics, Mathematics, Computer Science, or Economics. • Master’s degree or PhD is an added advantage. • 2–5 years of experience in data science, product analytics, or digital experimentation roles, with a strong focus on A/B testing and website optimization.