Operations Research Intern Optimization & Risk Modeling
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Job Location:
Monthly Salary:
Posted on:
3 days ago
Vacancies:
1 Vacancy
Job Summary
About Pelico
We are creating the factory of the future where disruptions are avoided processes synchronized and value captured. Our factory operations management platform enables factory teams to be more agile and resilient in a world where supply chain disruptions occur every 16 minutes. Pelico empowers users to identify bottlenecks avoid problems and focus on innovation instead of fire-fighting. Since our foundation in 2019 weve partnered with industry leaders across aerospace industrial equipment and luxury watchmaking revolutionizing factory operations in over 15 countries. Esteemed clients include Airbus Safran Cartier Daikin and Eaton.
Our Team
With a dynamic team of over 140 professionals across the US and France Pelico is a melting pot of top-tier talent from Tech Data Science and Manufacturing domains. Our collaborative environment fosters innovation and excellence driving us to solve complex challenges and shape the future of manufacturing. Our work has been recognized by Safran (Digital Transformation Award) and Microsoft (scale-up of the year).
Context
Modern manufacturing organizations face increasing volatility: changing demand supplier delays capacity constraints and complex multi-level BOMs make it extremely difficult to plan supply and production in a reliable and agile way. Traditional planning systems often fail to capture real-world uncertainty resulting in late orders shortages and firefighting on the shop floor.
Pelico is building an AI-driven platform that bridges the gap between planning and execution enabling teams to anticipate problems earlier simulate scenarios and orchestrate recovery actions.
Missions
Part 1 - Optimization of stock flow and pegging strategies (in a deterministic setting)
The first part focuses on improving how available supply is allocated to downstream needs using optimized pegging and allocation strategies. Today Pelico relies on a deterministic allocation rule (FIFO); this internship aims to evaluate alternative allocation policies that maximize service level & revenue while minimizing WIP premature builds and excess inventory.
You will explore different objective functions and constraints such as:
maximizing revenue order coverage and OTIF
minimizing inventory or early builds
integrating safety constraints
Part 2 - Risk assessment and uncertainty modeling from historical data
The second part studies how uncertainty can be formally quantified to support more robust decision-making in the future. The goal is to build a risk assessment layer that characterizes plant parts supply events or pegging links based on historical behavior considering volatility in supply lead times and quantities demand variability production cycle time uncertainty and historical shortage patterns.
This includes:
collecting and structuring historical data
building indicators
estimating shortage or lateness probabilities
propagating uncertainty through the pegging graph
evaluating whether current safety stocks or safety times are adequate.
In essence this part creates the risk intelligence needed to later enhance the optimized policies explored in part 1.
During this internship you will:
Conduct a literature review and benchmark of state-of-the-art methods.
Formalize the problem propose modeling assumptions and design candidate algorithms.
Build and iterate on a prototype.
Evaluate your approach on real-world industrial datasets from Pelico customers.
Collaborate with PMs and engineers to challenge assumptions and refine the modelling direction based on your results.
Document your work clearly and share learnings with the team.
Expected Outcomes
A working algorithmic prototype demonstrating the proposed approach.
A quantitative evaluation comparing different methods and highlighting trade-offs.
Clear recommendations for productization including limitations and assumptions.
Success means producing a method that is sound explainable and applicable at industrial scale strong enough to influence Pelicos roadmap or be integrated into our platform.
Depending on performance and interest the internship may lead to a full-time offer.
What you will learn
How to apply advanced optimization and stochastic methods to real industrial planning & orchestration problems.
How to turn research into impact: from algorithm design to prototyping testing and integration into a production-grade SaaS platform.
What it means to work in a fast-growing SaaS scale-up building the next generation of solutions bridging the gap between planning and execution.
What we offer
Work on a highly impactful product that users love!
Office location at the heart of Paris (75002)
Remote flexibility while autonomous
1 paid leave/month worked
Any additonal days related to graduation (presentation oral rattrapage)
50% meal allowance: 10/day worked (Swile card)
100% public transportation or equivalent in sustainable mobility package
Afterwork every quarter
Key Skills
- Robotics
- Machine Learning
- Python
- AI
- C/C++
- Data Collection
- Research Experience
- Signal Processing
- Natural Language Processing
- Computer Vision
- Deep Learning
- Tensorflow
