Partner with business leaders to identify high-value opportunities, formulate requirements and rationalize analytical approaches to solve them
Develop a firm understanding of specific business processes and real-world workflows, which may include manufacturing, supply chain, accounting and other related functions
Work closely with cross-functional teams including domain experts, business analysts, data engineers and software engineers
Lead data science initiatives that impact operations across multiple business units and global regions
Define project scope, timelines and deliverables in collaboration with business leaders
Architect scalable machine learning and AI 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.
Present clear, compelling visualizations and executive summaries tailored to non-technical audiences
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
SUGGESTED QUALIFICATIONS
Master's degree in a quantitative discipline
Five or more years of professional data science experience, with a track record of leading high-impact projects
Proven ability to communicate complex or technical concepts clearly to both technical and non-technical audiences
Advanced proficiency in Python, SQL and PySpark
Deep expertise in machine learning, deep learning, optimization, and statistical modeling
Familiarity with emerging trends such as generative AI and responsible AI
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
Strong understanding of manufacturing operations, supply chain optimization and ERP systems
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