Senior Data Scientist

As a Senior Data Scientist , you will:

- 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