Data Scientist

Data Scientist

Experience:

📍 Locations: Noida

Must Have Required Skills:

Minimum 2+year of experience in data science roles with exposure to: AI/ML pipelines, predictive modelling, Optimization techniques or industrial scheduling .

• Proficiency in Python, especially with: pandas, numpy, scikit-learn ortools, pulp, cvxpy or other optimization libraries, matplotlib, plotly for visualization
• Solid understanding of: Production planning & control processes (dispatching rules, job-shop scheduling, etc.), Machine Learning fundamentals (regression, classification, clustering)
• Familiarity with version control (Git), Jupyter/VSCode environments, and CI/CD principles 

Preferred (Nice-to-Have) Skills:

• Time-series analysis, sensor data, or anomaly detection, Manufacturing execution systems (MES), SCADA, PLC logs, or OPC UA data, Simulation tools (SimPy, Arena, FlexSim) or digital twin technologies
• Exposure to containerization (Docker) and model deployment (FastAPI, Flask)
• Understanding of lean manufacturing principles, Theory of Constraints, or Six Sigma

Key Responsibilities:

1. AI-Based Scheduling Algorithm Development

Develop and refine scheduling models using:

• Constraint Programming  Mixed Integer Programming (MIP)
• Metaheuristic Algorithms (e.g., Genetic Algorithm, Ant Colony, Simulated Annealing)
• Reinforcement Learning or Deep Q-Learning
• Translate shop floor constraints (machines, manpower, sequence dependencies, changeovers) into mathematical models.

2. Data Exploration & Feature Engineering

• Analyze structured and semi-structured production data from MES, SCADA, ERP, and other sources.
• Build pipelines for data preprocessing, normalization, and handling missing values.
• Perform feature engineering to capture important relationships like setup times, cycle duration, and bottlenecks.

3. Model Validation & Deployment

• Use statistical metrics and domain KPIs (e.g., throughput, utilization, makespan, WIP) to validate scheduling outcomes.
• Deploy solutions using APIs, dashboards (Streamlit, Dash), or via integration with existing production systems.
• Support ongoing maintenance, updates, and performance tuning of deployed models.

4. Collaboration & Stakeholder Engagement

• Work closely with production managers, planners, and domain experts to understand real world constraints and validate model results.
• Document solution approaches, model assumptions, and provide technical training to stakeholders.

Qualifications:

Bachelor’s or Master’s degree in: Data Science, Computer Science, Industrial Engineering, Operations Research, Applied Mathematics, or equivalent. 

🌐 To know more about us Visit : https://algo8.ai/

📧 Interested Applicants can share the resume: smita.choudhury@algo8.ai