Growth Data Scientist employed at Mercari to drive ML initiatives for business impact and user engagement.
About the role
- Senior Data Scientist leading data science initiatives impacting global operations across various business units. Collaborating with cross-functional teams to architect scalable machine learning solutions in cloud environments.
Responsibilities
- Partner with business leaders to identify high-value opportunities in areas such as demand planning, capacity/production planning, procurement, and financial forecasting
- Develop a firm understanding of specific business processes and real-world workflows
- Work closely with cross-functional teams including domain experts, business analysts, data engineers and software engineers
- Lead data science initiatives that impact operations globally across multiple business units
- Define project scope, timelines and deliverables in collaboration with business leaders
- Architect scalable machine learning and forecasting solutions within cloud platforms such as AWS, Azure, Databricks, and Snowflake
- Ensure models are production-ready, robust, and maintainable with appropriate monitoring and retraining pipelines
- Develop standardized methodologies and frameworks to ensure scalability and consistency across diverse environments
- Ensure compliance with data governance, privacy, and security standards while scaling analytics solutions globally
- Manage and mentor interns, junior data scientists and analysts
- Translate advanced analytics results into strategic recommendations for VP and C-level leadership
- Utilize programming languages such as SQL, Python for data manipulation, analysis and model development
Requirements
- Master’s degree in a quantitative discipline
- Five or more years of professional data science experience in manufacturing and/or supply chain environments
- Hands-on experience working with ERP data and operational processes including order-to-cash, procure-to-pay, and demand-to-deliver
- Proven ability to communicate complex or technical concepts clearly to both technical and non-technical audiences
- Advanced proficiency in Python, SQL and PySpark; experience wrangling large relational datasets
- Deep expertise in machine learning, forecasting and optimization
- Experience deploying enterprise-scale solutions in cloud environments (AWS experience preferred)
- Proficient in at least one data visualization library such as Matplotlib, Seaborn, or Plotly
- Knowledge of Streamlit for building interactive data applications preferred
- Familiarity with MLOps practices, CI/CD pipelines, and model lifecycle management
- Demonstrated ability to drive business impact and ROI through analytics
- Strong track record of executive-level communication and influence
- Experience leading cross-functional teams across multiple geographies
Job title
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