Optimization Scientist – Route & Inventory Optimization (OR & RL)

at WINIT

Optimization Scientist – Route & Inventory Optimization (OR & RL)

WINIT

Company

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Optimization Scientist – Route & Inventory Optimization (OR & RL)

at WINIT

Posted by Aishwarya SURENDRAN

1 - 3 yrs

₹4L - ₹6L / yr

Hyderabad

Skills

route optimization,

Forecasting

MILP

RL algorithms

Python

NumPy

pandas

TensorFlow

Job Title: Optimization Scientist – Route & Inventory Optimization (OR & RL)

Location: Hyderabad (On-site)

Experience Required: 1+ year

Company Overview:

We are a leading AI-driven supply chain solutions company focused on transforming retail, FMCG, and logistics through cutting-edge technologies in machine learning, operations research, and reinforcement learning. Our mission is to build intelligent systems that enhance decision-making and automate processes across forecasting, inventory, and transportation.

Internship Overview:

We are seeking a passionate and motivated AI/ML Intern to support the development of intelligent optimization systems for route planning and inventory allocation. You will work alongside experienced scientists and engineers, gaining hands-on experience in applying machine learning, reinforcement learning, and operations research to real-world logistics challenges.

Key Responsibilities:

🔹 Assist in Route Optimization Projects:

Support in modeling and solving simplified versions of Vehicle Routing Problems (VRP) under guidance.
Work with Python libraries like Pyomo or OR-Tools to prototype optimization solutions.
Explore reinforcement learning methods (e.g., DQN, PPO) for dynamic routing decisions under uncertainty.

🔹 Support Inventory Optimization Efforts:

Learn to model multi-echelon inventory systems using basic OR and simulation techniques.
Analyze historical data to understand stock levels, service times, and demand variability.
Help design experiments to evaluate replenishment strategies and stocking policies.

🔹 Contribute to AI-Driven Decision Systems:

Assist in integrating ML forecasting models with optimization pipelines.
Participate in the development or testing of simulation environments for training RL agents.
Collaborate with the team to evaluate model performance using historical or synthetic datasets.

Required Qualifications:

Currently pursuing or recently completed a degree in Computer Science, Data Science, Operations Research, Industrial Engineering, or related field.
Good understanding of Python and key libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
Familiarity with basic optimization concepts (LP/MILP) and libraries like OR-Tools or Gurobi (student license).
Basic knowledge of reinforcement learning frameworks (OpenAI Gym, Stable-Baselines3) is a plus.
Strong problem-solving skills and willingness to learn advanced AI/OR techniques.

What You’ll Gain:

Hands-on exposure to real-world AI and optimization use cases in logistics and supply chain.
Mentorship from experienced scientists in OR, ML, and RL.
Experience working in a fast-paced, applied research environment.
Opportunity to convert to a full-time role based on performance and business needs.

About WINIT:

WINIT is a pioneer in mobile Sales Force Automation (mSFA) with over 25 years of experience. We serve more than 600 global enterprises, helping them enhance efficiency, streamline logistics, and leverage AI/ML to optimize sales operations. With a commitment to innovation and global support, WINIT continues to lead digital transformation in sales.

Job Title: Optimization Scientist – Route & Inventory Optimization (OR & RL)

Location: Hyderabad (On-site)

Experience Required: 1+ year

Company Overview:

Internship Overview:

Key Responsibilities:

🔹 Assist in Route Optimization Projects:

Support in modeling and solving simplified versions of Vehicle Routing Problems (VRP) under guidance.
Work with Python libraries like Pyomo or OR-Tools to prototype optimization solutions.
Explore reinforcement learning methods (e.g., DQN, PPO) for dynamic routing decisions under uncertainty.

🔹 Support Inventory Optimization Efforts:

Learn to model multi-echelon inventory systems using basic OR and simulation techniques.
Analyze historical data to understand stock levels, service times, and demand variability.
Help design experiments to evaluate replenishment strategies and stocking policies.

🔹 Contribute to AI-Driven Decision Systems:

Assist in integrating ML forecasting models with optimization pipelines.
Participate in the development or testing of simulation environments for training RL agents.
Collaborate with the team to evaluate model performance using historical or synthetic datasets.

Required Qualifications:

Currently pursuing or recently completed a degree in Computer Science, Data Science, Operations Research, Industrial Engineering, or related field.
Good understanding of Python and key libraries (NumPy, Pandas, Matplotlib, Scikit-learn).
Familiarity with basic optimization concepts (LP/MILP) and libraries like OR-Tools or Gurobi (student license).
Basic knowledge of reinforcement learning frameworks (OpenAI Gym, Stable-Baselines3) is a plus.
Strong problem-solving skills and willingness to learn advanced AI/OR techniques.

What You’ll Gain:

Hands-on exposure to real-world AI and optimization use cases in logistics and supply chain.
Mentorship from experienced scientists in OR, ML, and RL.
Experience working in a fast-paced, applied research environment.
Opportunity to convert to a full-time role based on performance and business needs.

About WINIT:

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About WINIT

Founded :

1997

Type :

Product

Size :

20-100

Stage :

Profitable

About

N/A

Company social profiles

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