Note: The job is a remote job and is open to candidates in USA. Golden Technology is seeking a senior data scientist to join a team focused on personalized customer experiences for a large U.S. e-commerce site. The role involves designing and improving search and recommender systems using machine learning and deep learning, evaluating model performance, building analytics pipelines, and collaborating with engineering, product, and business teams.
Responsibilities
- Design, develop, and implement recommender systems tailored to grocery retail and e-commerce personalization needs
- Build advanced machine learning and deep learning models to deliver personalized product, coupon, substitute, and recipe recommendations
- Define evaluation methods and key metrics to measure recommender system performance and identify areas for improvement
- Conduct A/B testing and offline model evaluations to compare recommendation strategies and improve model outcomes
- Perform root cause analysis and model interpretability reviews to understand recommendation results and improve accuracy
- Improve personalization by incorporating customer preferences, dietary needs, shopping behaviors, and engagement patterns
- Explore recommendation diversity strategies that expose customers to a broader range of relevant products while maintaining accuracy
- Partner with ML engineers to support model deployment, serving, versioning, and production pipeline best practices
- Collaborate with data scientists, data engineers, full stack engineers, product teams, and business stakeholders to deliver data science solutions
- Integrate transactional, customer, product, demographic, and user feedback data to support model development and analytics
- Build customer analytics pipelines, reporting dashboards, and performance tracking to monitor recommendation effectiveness over time
- Document best practices, technical insights, lessons learned, and model development approaches for internal knowledge sharing
- Contribute to internal tools, libraries, and documentation that support adoption and maintenance of recommender system solutions
- Participate in knowledge-sharing sessions and technical discussions to support continuous learning across the team
Skills
- 2+ years of proven experience building deep learning models for large-scale recommender systems
- Proficiency in ML frameworks such as TensorFlow or PyTorch
- Proficiency in SQL, Python and Spark for data analysis and manipulation
- Proficiency with statistics, design of experiments, exploratory data analysis, and insights generation
- Experience working with cloud platforms like Azure or GCP
- High level of independence to develop and own toolkits, pipelines, and dashboards
- Excellent problem-solving skills and a proactive approach to addressing challenges
- Strong analytical and critical thinking skills with attention to detail
- Must be able to learn from others and teach others and work collaboratively as part of a highly interdependent team
- Ability to communicate complex ideas effectively to both technical and non-technical stakeholders
- Experience working with Databricks is a plus
- Experience working with Data Engineering and MLOps is desirable
- Prior experience in the retail or e-commerce industry is a plus
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