Key Responsibilities
- Build predictive models and advanced analytics solutions to improve personalization, recommendation, and customer segmentation.
- Analyze large-scale datasets to identify behavioral trends, business opportunities, and product improvement areas.
- Partner with data engineers to ensure clean, reliable, and accessible data for experimentation and model deployment.
- Design and run A/B tests to measure the impact of algorithms and product features.
- Translate technical insights into clear, actionable recommendations for business and product stakeholders.
- Stay current with research and industry best practices in machine learning, NLP, and AI, applying them to real-world e-commerce challenges.
Qualifications
- Master's degree or higher in Data Science, Statistics, Computer Science, or a related field.
- 3+ years of experience in data science, machine learning, or applied analytics.
- Proficiency in Python, R, or Scala, with strong skills in data analysis and statistical modeling.
- Experience with ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn) and data visualization tools (e.g., Tableau, Power BI).
- Strong knowledge of A/B testing, experimentation design, and causal inference.
- Excellent communication skills, with the ability to present complex findings to non-technical stakeholders.
Preferred Qualifications
- Experience in global e-commerce, personalization, or recommendation systems.
- Familiarity with big data platforms (Spark, Hadoop) and cloud ML pipelines (AWS Sagemaker, GCP Vertex AI, or Azure ML).
- Background in NLP or computer vision applications for large-scale platforms.
At we're committed to building a diverse and inclusive workplace where everyone can thrive. We're proud to be an equal opportunity employer and make all employment decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, veteran status, or any other protected characteristic.