DESCRIPTION
Core responsibilities cover three pillars:
DIGITAL ANALYTICS: Lead a select number of strategic analyses to provide teams and leaders with actionable insights regarding opportunities to improve traffic, engagement, and conversion. Turn optimization hypotheses into A/B test proposals. Partner with Marcom Producers, Creatives, and Developers to determine the A/B test population, user experience, KPIs, and runtime requirements.
EXPERIMENT ANALYSIS: Design experiments, analyze results, develop insights, and summarize recommendations. Work closely with the A/B Test Platform Engineering Team to ensure the analytics implementation suits our needs.
RESEARCH & DEVELOPMENT: Partner with Data Scientists across Marcom, Retail, and Operations to increase the sophistication of our experimentation program and deliver deeper insights about marketing performance.
EDUCATION & EXPERIENCE: Bachelor’s degree with quantitative emphasis. Statistics, Data Science, Mathematics, Operations Research, Computer Science, Marketing Analytics, or related field. Master’s Degree desirable. Minimum 3-5 years of relevant industry experience.
Key points:
- The candidate should have minimum of 8 years of experience. Hands on.
- Being based in the Bay Area is a plus but not mandatory.
- Regular office visits (about once a week) significantly increase the likelihood of a long-term engagement.
- Experience as a Data Scientist in Production Systems (rather than Product Engineering) is beneficial.
- The ideal candidate is a business-facing consultant with in-depth experience in:
- Identifying testing opportunities.
- Creating hypotheses.
- Analyzing user behavior, data, and extracts.
- Generating business insights.
- Influencing business decisions based on data-driven inferences
Roles & Responsibilities :
ESSENTIAL QUALIFICATIONS
- Expertise in experimentation and statistical hypothesis testing (e.g., determining sample sizes/power analysis, applying statistical tests, confidence intervals).
- Strong communication and presentation abilities, with the skill to convey analyses to a wide range of stakeholders, including data scientists, creatives, and marketing leaders.
- Extensive experience in digital analytics, with the capability to extract insights from diverse quantitative and qualitative data sources.
- Proficiency in data querying (SQL) and familiarity with scripting languages such as Python or R.
- Excellent time management skills, with the ability to oversee multiple A/B testing projects in various stages of development.
- A team-oriented mindset, with a preference for collaborative work.
Highly advantageous:
- Experience in advanced statistics, econometrics, or causal inference.
- Familiarity with predictive analytics and machine learning algorithms, such as regression, decision trees, clustering, and neural networks.