Data Scientist

The Data Scientist is responsible for analyzing and interpreting complex datasets using statistical techniques, machine learning, and programming to generate actionable insights and solve business problems. This role partners with cross-functional teams to build predictive models, improve data quality, and support data-driven decision-making across the organization. This is an individual contributor role focused on hands-on technical execution rather than people management. Key Responsibilities

• Analyze large volumes of structured and unstructured data to identify trends and insights
• Develop and deploy predictive models and machine learning algorithms
• Utilize tools such as Python, R, Spark, and cloud-based platforms (e.g., Databricks)
• Create data visualizations and reports to communicate insights to technical and non-technical stakeholders
• Collaborate with data engineers, analysts, architects, and business stakeholders to define requirements and solutions
• Support data quality improvement efforts and troubleshoot data-related issues
• Lead or contribute to data science projects, analytics initiatives, and system integrations
• Document solutions and support tracking of incidents, changes, and enhancements
• Mentor team members on data science tools, techniques, and best practices
• Contribute to the development and execution of the data science roadmap

• Bachelors degree in a relevant field with 5+ years of experience, or
• Masters degree with 3+ years of experience
• Experience working with data science and analytics tools (Python, R, Spark, Databricks, etc.)
• Strong background in statistical analysis and machine learning
• Experience working with large datasets and complex data environments
• Strong problem-solving and analytical skills
• Ability to communicate insights clearly to technical and business audiences
• Experience collaborating across cross-functional teams

Preferred Qualifications

• Experience with Power BI or Microsoft Power Platform tools
• Familiarity with large language models (LLMs) and AI applications
• Experience with Retrieval-Augmented Generation (RAG) architectures
• Experience with front-end application development (e.g., Flask, Gradio)
• Advanced degree (Masters or PhD)

Industry Background

• Preferred experience in manufacturing, automotive, industrial, or engineering environments
• Open to candidates from adjacent industries such as healthcare, retail, or biotech
• Heavy financial services background is not preferred

Additional Information

• This is a hands-on individual contributor role (not a leadership or director-level position)
• Strong emphasis on supply chain-related data and business functions
• Opportunity to work on complex, high-impact data initiatives