Senior Data Scientist Manufacturing AnalyticsMacpower Digital Assets Edge Private Limited • United States
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Senior Data Scientist Manufacturing Analytics
Macpower Digital Assets Edge Private Limited
- United States
- United States
About
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:
Applied 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.
Languages
- English
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