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Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, or a related field.
4–8+ years of experience in Data Science, Machine Learning, or Analytics.
Strong programming skills in Python and SQL.
Experience with machine learning libraries such as Scikit-learn, TensorFlow, PyTorch, or XGBoost.
Strong understanding of statistics, probability, and predictive modeling.
Experience with data visualization tools such as Power BI, Tableau, or Matplotlib.
Hands-on experience with cloud platforms (AWS, Azure, or Google Cloud Platform).
Experience working with large datasets using Spark, Hadoop, or Databricks is a plus.
Knowledge of MLOps, model deployment, and CI/CD pipelines is preferred.
Excellent analytical, problem-solving, and communication skills.
Job ID: 150860821
Skills:
Predictive Modeling, Machine Learning, Amazon Web Services, Artificial Intelligence, Natural Language Processing, Apache Spark, Data Mining, Big Data, Deep Learning, Data Science, Algorithms, R Programming Language, Data Visualization, Python Programming Language, Tableau Business Intelligence Software, SQL Programming Language, Data Analysis, Statistical Modeling
Skills:
prophet , Machine Learning, Clustering, Deep Learning, Tensorflow, Numpy, Pandas, Pytorch, MLops, Arima, Python, LSTM, Predictive Models, Scikit-learn, Time-Series Analysis, Regression, anomaly detection, Predictive Maintenance Models, Classification, Data Analysis, Temporal CNNs
Skills:
Machine Learning, Hadoop, Power Bi, Tableau, Tensorflow, Hive, Pytorch, Time Series Analysis, Spark, Data Visualization, Forecasting Models, mathematical programming, MLlib, Scikit-learn, Clustering Models, Meta Heuristic Algorithms, combinatorial optimization, Stochastic Process, Mixed-Integer Programming, Data Analysis, Linear Programming
Skills:
Data Science, Machine Learning, Software Development, MLops, Cloud Architecture, Open Source Libraries, Ai
Skills:
metaheuristics , Spark SQL, Python, Simulation Models, Prompt engineering, LLMs, heuristics, GenAI ecosystems, tool-use orchestration, Linear Mixed Integer Programming, agent frameworks, MLOps deployment pipelines, Data pipelines, Multi-agent systems
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