Data Scientist – Pricing, Warranty and Cost Analytics

Assignment Overview

We are looking for a Data Scientist to solve complex business challenges within parts and contract pricing, warranty claim assessment, and cost-control analysis.

The role combines strong Python engineering skills with mathematical and statistical expertise. You will develop, deploy, maintain, and continuously improve practical data science solutions using both structured and unstructured data, including text and images.

You will work closely with Data Scientists, Data Engineers, and business stakeholders in an agile environment.

Key Responsibilities

• Explore and analyze data, translating business requirements into clearly defined data science problems and solutions.
• Develop, evaluate, and improve machine learning, deep learning, statistical, and optimization models.
• Build and maintain robust Python code and pipelines for model training and inference.
• Deploy and maintain containerized solutions using AWS SageMaker AI, AWS ECS, and Snowflake.
• Process and analyze data in Snowflake using Snowpark and SQL.
• Contribute to CI/CD pipelines, technical documentation, and shared development practices.
• Evaluate solution performance together with business stakeholders and drive continuous improvement.
• Collaborate within an agile team and contribute to technical decisions.
• Select appropriate technologies and analytical approaches based on business requirements.

Education — Must Have

• A degree or equivalent background in Computer Science, Physics, Mathematics, Statistics, or another quantitative field.
• Strong computational skills.

Experience — Must Have

• Strong Python programming and software development skills.
• Experience developing and applying machine learning or statistical models.
• Practical knowledge of Git and collaborative software development.

Experience — Nice to Have

• Experience with PyTorch or TensorFlow for deep learning.
• Experience with RAG and MCP, or a solid understanding of their practical application.
• Familiarity with Bash scripting.
• Experience with CI/CD, containerization, and deployment workflows.
• Experience with AWS services such as SageMaker AI, Bedrock, ECS, or EC2.
• Experience with Snowflake and Snowpark.
• Experience maintaining technical documentation using tools such as MkDocs and GitLab Pages.

Personal and Professional Skills

• Strong analytical and critical-thinking abilities.
• A curious, collaborative, and solution-oriented mindset.
• Ability to explain complex technical findings clearly to stakeholders from different backgrounds.
• Strong problem-solving skills and sound technical judgment.
• Confidence working across technical and business functions.
• Ability to select suitable tools and approaches based on business needs.

Technical Environment

• Core stack: Python, SQL, AWS SageMaker AI, AWS ECS, Snowflake, Snowpark, GitLab, Docker, Streamlit, and Bash
• AI and ML: PyTorch, AWS Bedrock, AgentCore, OpenAI, agentic AI, and AI-assisted coding agents
• Documentation: MkDocs and GitLab Pages

Strong coding fundamentals, sound judgment, and the ability to develop practical solutions are more important than experience with every technology in the stack.