Data Scientist and Experimentation Analyst

Summary

Join Encora as a Data Scientist & Experimentation Analyst and play a critical role in developing and evaluating machine learning (ML)-driven pricing and personalization solutions. You will provide data-driven insights and rigorous experimentation, offering end-to-end support for ML initiatives. This role requires expertise in statistical analysis, experiment design, and data science workflows. You will collaborate with ML Scientists, Data Engineers, and Product Managers. The ideal candidate will excel in supporting ML Scientists in building robust models and analyzing their performance. This is a remote position.

Requirements

• 7+ years in data science, experimentation analysis, or a related role supporting ML projects and experimentation
• Strong understanding of statistical methods, experiment design, and causal inference techniques
• Proficiency in Python for data manipulation & machine learning (Pandas, NumPy, sci-kit-learn)
• Intermediate skills in SQL for data querying, including Window Functions, Joins, and Group By
• Familiarity with classical ML techniques like Classification, Regression, and Clustering, using algorithms like XGBoost, Random Forest, and KMeans
• Experience with data visualization platforms (e.g., Tableau, Power BI, Matplotlib, or Seaborn)
• Proficiency in designing and analyzing A/B and multivariate experiments, focusing on drawing actionable insights
• Experience working with large, complex datasets, including preprocessing, feature engineering, and encoding techniques

Responsibilities

• Design, execute, and interpret controlled experiments (e.g., A/B tests, multivariate tests) to evaluate the effectiveness of ML models and strategies
• Conduct exploratory data analysis (EDA), hypothesis testing, and statistical modelling to support ML and business objectives
• Assist ML Scientists in preparing data, engineering features, and evaluating models for pricing and personalization solutions
• Create dashboards and visualizations to track key metrics, experiment outcomes, and model performance
• Perform deep dives and provide actionable insights on specific datasets or business questions to inform strategic decisions
• Partner with ML Scientists, Data Engineers, and Product Managers to align on experimentation goals and ensure successful implementation of ML solutions