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Designs portions of engineering solutions utilizing multiple engineering disciplines for products, systems, software, and solutions based on established engineering principles and in accordance with provided specifications and requirements Implements established test plans for existing designs, including validation of mechanical, electrical, software, and other engineering specifications and requirements. Develops understanding of and relationship with internal and outsourced development partners on engineering design and development. Participates as a member of project team of other engineers and internal and outsourced development partners to develop reliable, cost effective and high quality solutions for low to moderately- complex products.

Design and develop responsive, user-friendly frontend interfaces using React.js Build and maintain RESTful APIs and backend services using Python (Flask or Django) Integrate frontend applications with backend services and third-party APIs Work with relational and/or NoSQL databases (MySQL / MongoDB) for data modeling and queries Write clean, maintainable, and well-documented code Participate in code reviews, testing (including manual and API testing via tools like Postman), and debugging

Partner with global Trade Compliance and Operations teams to support adherence to international trade regulations Prepare, validate, and maintain documentation required for global trade compliance and shipment processing Contribute to audit readiness activities and support compliance monitoring efforts Collaborate with cross-functional stakeholders to resolve trade-related challenges effectively Develop certification documentation for approval by global trade leadership Engage with suppliers to assess eligibility and compliance with Free Trade Agreement (FTA) requirements Design and maintain dashboards, scorecards, and KPI reports using Power BI and Excel

The ability to explain a technical decision to somebody who did not make it. Every round here includes it.

Core Data Science - strong foundation in statistics, probability, ML/DL algorithms, and model evaluation techniques Python & SQL - solid proficiency; you think in Python and speak fluent SQL ML Toolkit - hands-on experience with Pandas, NumPy, Scikit-learn, and at least one deep learning framework (PyTorch / TensorFlow) Generative AI & LLMs - working knowledge of large language models (GPT, LLaMA, etc.), prompt engineering, and prompt optimization techniques RAG & Embeddings - understanding of Retrieval-Augmented Generation architectures, vector databases (FAISS, Pinecone, Weaviate), and embedding strategies LLM Frameworks - exposure to LangChain, LangGraph, or similar orchestration frameworks Communication - ability to distill complex analysis into clear insights for both technical and non-technical audiences Mindset - strong problem-solving instincts, intellectual curiosity, and a bias for action.

Understand business problems and translate them into data science solutions. Analyse data, build features, and develop ML/AI models. Deploy, monitor, and improve production models. Communicate insights and recommendations to stakeholders. Collaborate with data engineering, product, and business teams.