Data Scientist - Manufacturing,Aeropsace

1. Data Collection & Preparation Gather data from databases, APIs, ERP systems, CRM systems, and external sources. Clean, validate, and transform large datasets for analysis. Perform Exploratory Data Analysis (EDA) to identify trends and patterns.

2. Machine Learning Model Development Build, train, and deploy Machine Learning (ML) models. Develop predictive models for forecasting, classification, and recommendation systems. Tune model parameters to improve accuracy and performance.

3. Statistical Analysis Apply statistical techniques to solve business problems. Perform hypothesis testing, regression analysis, and forecasting. Identify key business drivers through data analysis.

4. Data Visualization & Reporting Create dashboards and reports using Power BI, Tableau, or Python. Present insights and recommendations to management and stakeholders. Convert complex data into actionable business decisions.

5. Business Problem Solving,Work closely with business teams to understand requirements.Translate business challenges into analytical solutions.Measure and optimize business performance using data-driven approaches.

6. Model Deployment & Monitoring Deploy models into production environments. Monitor model performance and retrain when necessary. Ensure scalability and reliability of deployed solutions.

7. Collaboration & Documentation Collaborate with Data Engineers, Business Analysts, and IT teams. Document methodologies, models, and findings. Follow data governance and security policies.

• Programming: Python, R, SQL
• Machine Learning: Scikit-learn, TensorFlow, PyTorch
• Data Analysis: Pandas, NumPy, SciPy
• Visualization: Power BI, Tableau, Matplotlib, Seaborn
• Databases: SQL Server, MySQL, PostgreSQL, MongoDB
• Cloud Platforms: Azure, AWS, GCP
• Big Data: Spark, Hadoop (preferred)