Senior Data Scientist

• Support the design and execution of A/B tests, multivariate experiments, and randomized controlled trials (RCTs) to assess the impact of product changes, marketing campaigns, and customer experiences.
• Develop and implement robust methodologies to measure the effectiveness of business initiatives (e.g., website features, promotions, UI changes, etc.) using experimentation frameworks.
• Own the end-to-end experimentation pipeline, including hypothesis generation, experimental design, implementation, monitoring, and post-experiment analysis.
• Identify and mitigate biases in experiment design and results, ensuring statistical rigor and reliability.

• Conduct advanced statistical analysis (e.g., causal inference, Bayesian analysis, regression modelling) to derive actionable insights from experimentation results.
• Develop and refine models to predict customer behavior and optimize conversion rates, retention, and other key business metrics.
• Analyze large-scale datasets and design efficient algorithms to support decision-making in areas like pricing, product recommendations, and personalization.

• Stay current with the latest advancements in data science, statistics, and experimentation methodologies.
• Propose innovative approaches to enhance the experimentation framework, such as new experimental designs, alternative modelling techniques, or improved metrics.
• Lead or participate in research to explore new ways of measuring and optimizing the customer journey in a retail/e-commerce setting.

• Education : Ph.D. or master s degree in Data Science, Statistics, Mathematics, Computer Science, Economics, or a related field.

Experience :

• 5+ years of professional experience in data science, with at least 2 years focused on experimentation, A/B testing, and causal inference in a retail or e-commerce environment.
• Proven track record of designing and analyzing large-scale A/B tests and experiments with demonstrable business impact.
• Strong experience with statistical analysis and modelling techniques, including hypothesis testing, regression analysis, and Bayesian statistics.
• Proficiency in data analysis tools (Python, R, SQL, etc.) and experimentation platforms (e.g., Optimizely, Google Optimize, or in-house experimentation tools).

Skills :

• Advanced knowledge of statistical methodologies for experiment design, analysis, and causal inference.
• Expertise in statistical software/tools such as Python, R , SQL , and experience with machine learning frameworks (e.g., TensorFlow , scikit-learn ).
• Strong communication skills, with the ability to explain complex technical concepts to non-technical stakeholders and executive leadership.
• Solid understanding of e-commerce and retail metrics (e.g., conversion rate, customer lifetime value, churn, etc.) and how they relate to experimentation.

• Experience with large-scale e-commerce platforms and digital product development.
• Familiarity with the advanced causal and inferential analytics
• Experience with advanced techniques in machine learning or AI that complement experimentation (e.g., recommender systems, predictive modelling).
• Familiarity with cloud-based platforms (e.g., AWS , Google Cloud , Azure ).
• Experience working in an agile environment and collaborating with cross-functional teams in a fast-paced business setting.