What are the responsibilities and job description for the Experimentation Data Scientist position at ePATHUSA Inc?
Seeking an Experimentation Data Scientist to play a key role in providing insights for business decision making that will directly impact product development, user experience and growth. Candidate will partner with devlopers, designers, product and the Experimentation Platform partners to identify and implement improvements through the AB testing lifecycle, ensuring smooth testing and analysis at scale. Job responsibilities include:
Collaborating with cross-functional teams such as product managers, engineer, and designers to define clear hypotheses, select appropratie metrics and design-controlled experiments
- Collect, clean, and transform data from various sources and conduct rigourous statistical anlyses to evaluation experiement results, identify trends and draw actionable insights
- Develop and apply statistical models to assess treatement effects, quantify uncertainty, and estimate casual impacts
- Create compelling visualizations to communicate experiment findings and insights to both tecnical and non-technical stakeholders
- Work closely with statkeholders to understand business goals, provide recommendations and iterate on experiment
- Collaborate and share work proactively to share best practicces and consistenly seek feedback to refine your approach
Stay up-to-date with advancements in experimental design, statistical tech niques and data science methodologies -
Requirements
- Bachelors degree in quantitative field ((Statistics, Computer Science, Mathematics, or related discipline) Graduate degree preferred
- Minimum of 3 years of experience in data science, with a focus on experimentation
- Proficiency in SQL and statistical programming (Python and/or R). Familiarity with PySpark is a plus
- Experience with supporting and designing AB tests at scale to drive product development
- Passion for developing and streamlining reliable tools to deliver insights with a high degree of automation
- Utilize regression analysis techniques (linear regression, logistic regression, etc.)
- Strong communication skills to convey complex findings to technical and non-technical audiences
- Experience with A/B testing platforms (e.g., Optimizely, Google Optimize, Adobe Target) is a plus
- 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
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