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.