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Data Science Intern

Lexlabs AI
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Compensation: Converted to paid role post training

 

🚀 About the Role

We're looking for a Data Science, Engineering Intern to help build intelligent systems that optimize the most chaotic part of construction and logistics: supply chain coordination. You'll work alongside our AI and product teams to develop models, simulations, and heuristics that reduce delays, improve vendor efficiency, and enable just-in-time execution.

This isn’t just building dashboards—we're modeling real-world complexity and turning it into AI-powered decision engines.

 

🛠️ What You’ll Do

Analyze real-world supply chain and logistics data from construction and vendor workflows

Build predictive models for material delays, vendor performance, and site bottlenecks

Contribute to route, task, or schedule optimization using algorithms (e.g., constraint programming, metaheuristics, cuOpt, OR-Tools)

Prototype simulations for dynamic scheduling, re-sequencing, and delay forecasting

Collaborate with ML engineers to integrate models into production workflows

Present insights to technical and business stakeholders with clear narratives

 

📚 What We’re Looking For

Currently pursuing a degree in Data Science, Computer Science, Industrial Engineering, or a related field

Strong Python skills; experience with NumPy, pandas, scikit-learn, and Jupyter Notebooks

Exposure to optimization libraries (e.g., PuLP, OR-Tools, SimPy, Gurobi, or cuOpt a plus)

Solid understanding of probability, statistics, and machine learning

Familiarity with supply chain or operations research concepts preferred

Curious mindset and ability to turn ambiguity into structured experiments

 

💡 Bonus Points

Experience with geospatial data, construction tech, or logistics systems

Knowledge of APIs, SQL, or cloud platforms (AWS, GCP, or Azure)

Prior hackathon, research, or project work related to logistics or supply chain optimization

 

🌱 What You’ll Gain

Exposure to real-time decision-making challenges in the physical world

Experience building models that actually get deployed—not just theorized

Mentorship from AI/ML engineers and domain experts in construction logistics

Opportunity to convert to full-time or continue part-time during the school year

 

📩 How to Apply

Apply via Handshake