Data Scientist: ML, NLP & Production Models

Cloud Analytics Technologies, LLC; San Francisco (CA); In loco; USD 120.000 - 180.000; Tempo pieno

Descrizione del lavoro

Cloud Analytics Technologies, LLC is seeking a Data Scientist to develop advanced analytical models, NLP solutions, and predictive algorithms. The role emphasizes Python, machine learning, and model deployment across production environments.

You will collaborate with data engineers, product teams, and stakeholders to drive data-driven decisions, perform advanced analytics, and continuously improve model performance on large-scale datasets.

Competenze

• Strong Python ML stack experience.
• Proficient in Pandas, NumPy, SciPy for data manipulation and analysis.
• Hands-on ML with Scikit-learn; deep learning with TensorFlow or PyTorch.

Mansioni

• Develop and implement machine learning models for predictive analytics.
• Perform exploratory data analysis to find patterns in complex datasets.
• Build classification, regression, and clustering models.
• Develop NLP solutions for text processing and sentiment analysis.
• Apply statistical techniques to support data-driven decisions.
• Feature engineering, model selection, and hyperparameter tuning.
• Develop model evaluation frameworks to measure accuracy and performance.
• Work with large datasets using Python and distributed computing tools.
• Deploy machine learning models into production environments.
• Collaborate with data engineers, product teams, and business stakeholders.
• Monitor model performance and implement improvements.
• Present analytical findings and recommendations.

Conoscenze

Python

Pandas/Numpy/Scipy

Scikit-learn

TensorFlow/PyTorch

Statistics

NLP

SQL

Data Visualization

Model Deployment

Git & Docker

Strumenti

Flask

FastAPI

Docker

Git

Descrizione del lavoro

Cloud Analytics Technologies, LLC is seeking a Data Scientist to develop advanced analytical models, NLP solutions, and predictive algorithms. The role emphasizes Python, machine learning, and model deployment across production environments.

You will collaborate with data engineers, product teams, and stakeholders to drive data-driven decisions, perform advanced analytics, and continuously improve model performance on large-scale datasets.