We are seeking an Experimentation Data Scientist to join our Experimentation team and play a key role in providing insights for business decision making that will directly impact product development, user experience, and growth at our client. You will partner with developers, designers, product, and our Experimentation Platform partners to identify and implement improvements throughout the AB testing lifecycle, ensuring smooth testing and analysis at scale.
Responsibilities
• Experimental Design: Collaborate with cross-functional teams (product managers, engineers, designers) to define clear hypotheses, select appropriate metrics, and design-controlled experiments (A/B tests, multivariate tests, etc.).
• Data Collection and Analysis: Collect, clean, and transform data from various sources. Conduct rigorous statistical analyses to evaluate experiment results, identify trends, and draw actionable insights.
• Statistical Modeling: Develop and apply statistical models to assess treatment effects, quantify uncertainty, and estimate causal impacts. Familiarity with addressing non-normal data distribution.
• Data Visualization: Create compelling visualizations to communicate experiment findings and insights to both technical and non-technical stakeholders.
• Collaboration: Work closely with stakeholders to understand business goals, provide recommendations, and iterate on experiments. Collaborate and share your work proactively to share best practices and consistently seek feedback to refine your approach.
• Continuous Learning: Stay up-to-date with advancements in experimental design, statistical techniques, and data science methodologies.
Qualifications
• Education: Bachelor’s degree in a quantitative field (Statistics, Computer Science, Mathematics, or related discipline). Graduate degree preferred.
• Experience:
o Minimum of 3 years of experience in data science, with a focus on experimentation.
o Proficiency in SQL and statistical programming (Python and/or R). Familiarity with PySpark is a plus
o Experience with supporting and designing AB tests at scale to drive product development
o Passion for developing and streamlining reliable tools to deliver insights with a high degree of automation.
o Utilize regression analysis techniques (linear regression, logistic regression, etc.)
o Strong communication skills to convey complex findings to technical and non-technical audiences
o Experience with A/B testing platforms (e.g., Optimizely, Google Optimize, Adobe Target) is a plus.
o Comfort with ambiguity; ability to thrive with minimal oversight and process.
• Analytical Mindset: Ability to think critically, ask insightful questions, and approach problems from a data-driven perspective.
• Team Player: Collaborative, adaptable, and eager to contribute to a fast-paced, innovative environment.
