Senior AI & Data Engineer - Strategy & Operational Intelligence

PackageX is developing a cutting-edge Physical Logistics Execution Platform designed for enterprise teams managing manufacturing sites, distribution centers, warehouses, retail locations, and other logistics-intensive environments. Leveraging Vision AI, workflow automation, mobile execution, and seamless integrations, the platform enables companies to digitize, execute, and verify physical operations at the point of work. This approach creates trusted evidence of operational activities, supporting better decision-making through a simple operating model: Execution, Verification, and Evidence.

The company is seeking a Senior AI & Data Engineer specializing in Strategy and Operational Intelligence. This role goes beyond traditional model building to uncover hidden patterns, fee anomalies, and cross-dataset connections that influence business decisions. The ideal candidate is not just a dashboard maintainer but a strategic thinker who asks “why” before “how,” transforming raw data into compelling narratives for leadership, product, and operations teams. You will work hands-on with platform data, customer operations, and warehouse workflows, mining large datasets, building and deploying machine learning models, designing data pipelines, and delivering actionable insights to stakeholders.

This senior position requires a blend of rigorous data science, strong engineering skills, and effective communication. You will act as a strategic intelligence partner, owning projects end-to-end—from raw data to production systems and executive presentations. A technical product owner mindset is essential, meaning you will define problems worth solving, establish success metrics before building, and treat every model, pipeline, and dashboard as a product with users and adoption goals.

Key Responsibilities

- Own the roadmap and prioritize data science and machine learning initiatives based on business impact.
- Define problems, requirements, and success metrics for all data products.
- Generate insights from operational, customer, and platform data, identifying fee anomalies, cost drivers, and cross-domain patterns.
- Design, develop, and deploy ML and deep learning models for NLP and predictive analytics.
- Build reproducible, performant, and production-ready ML frameworks and services.
- Architect ETL pipelines, data warehouses, and data models to support scalable analytics.
- Develop and expose data services via RESTful APIs deployed on AWS or GCP.
- Create analytics dashboards and tools for leadership, operations, and partner teams.
- Present data narratives clearly to both technical and non-technical audiences.
- Maintain data quality, documentation, and engineering best practices.
- Automate manual data workflows and improve scalability.
- Track adoption and business impact of models and dashboards, iterating or retiring as needed.
- Collaborate with data analysts, ML engineers, and business stakeholders to align models with strategic needs.
- Deliver bug fixes and enhancements promptly with minimal supervision.

Required Qualifications

- 5+ years of experience as a data scientist, ML engineer, or data engineer working on production-grade systems.
- Expert proficiency in Python (including Pandas, NumPy) and SQL for complex data processing and analysis.
- Hands-on experience with TensorFlow, Keras, and/or PyTorch.
- Deep understanding of NLP and modern deep learning algorithms.
- Proven ability to discover insights that influence business decisions, beyond just building models.
- Strong backend development skills with Django and Flask, including RESTful API design and integration.
- Experience designing ETL pipelines, data warehousing, and data modeling for relational and NoSQL databases.
- Familiarity with GitHub, AWS, GCP, Docker, and CI/CD pipelines.
- Proficiency in analytics and visualization tools such as Tableau, Power BI, Matplotlib, and Seaborn.
- Excellent communication skills to engage with business leaders, product teams, and operations.
- Self-directed and proactive, comfortable working in fast-paced, ambiguous environments.
- Strong curiosity about logistics, supply chain, warehousing, and physical operations.

PackageX values candidates who can seamlessly switch between deep analytical insight and hands-on engineering, driving impactful data products from concept to production. This role offers the opportunity to influence strategic decisions across the company by transforming complex logistics data into clear, actionable intelligence.