Job Summary : We are seeking a highly experienced Data Scientist to join our analytics team, with a focus on advanced data modeling and AI applications in manufacturing. This role requires strong expertise in statistical modeling, machine learning, and time series analysis, coupled with a solid foundation in programming and data manipulation.
Key Responsibilities :
- Data Analysis : Analyze large, complex datasets to uncover actionable insights for business and manufacturing operations.
- Model Development : Design and implement machine learning models, including predictive and statistical models (e.g., regression, classification, clustering).
- Time Series Modeling : Build and validate models using time-series data for forecasting and anomaly detection in industrial environments.
- Visualization : Create dashboards and reports to visualize key metrics using tools such as Matplotlib and Seaborn.
- Collaboration : Partner with cross-functional teams-engineering, product, marketing-to gather requirements and deliver high-impact data solutions.
- Data Quality : Ensure data integrity through preprocessing, cleaning, and validation routines.
- Reporting : Communicate findings to stakeholders through presentations and documentation.
Required Qualifications :
Master's or Ph.D. in Data Science, Computer Science, Statistics, or a related discipline.5+ years of experience in data science or analytics roles.Proficiency in Python or R.Experience with statistical / empirical model building.Strong knowledge of machine learning techniques : regression, classification, clustering, neural networks.Extensive experience with time series data modeling and analysis.Hands-on experience with Python libraries : pandas, NumPy, SciPy.Experience with SQL and relational databases.Familiarity with data visualization tools such as Matplotlib and Seaborn.Preferred Skills :
pplied experience in manufacturing environments or industrial analytics.Experience deploying AI solutions in production systems.Knowledge of big data technologies : Hadoop, Spark.Cloud platform exposure (AWS, Google Cloud, Azure).Familiarity with version control systems like Git.