Data Scientist: ML, NLP & Production Deployments

Valiant Technologies LLC; San Francisco (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Valiant Technologies LLC is seeking a Data Scientist in San Francisco to develop advanced analytical models, machine learning solutions, and predictive algorithms to solve business problems. The role emphasizes Python, NLP, statistics, and scalable model deployment.

The ideal candidate will deploy models to production, collaborate with data engineers and product teams, and communicate technical findings to stakeholders for data-driven decisions.

Qualifications

• Strong programming experience in Python.
• Hands-on with Pandas/NumPy/SciPy.
• Expertise in Scikit-learn ML algorithms.
• Experience with TensorFlow or PyTorch.
• Knowledge of SQL and data visualization.
• Experience deploying models with Flask/FastAPI.

Responsibilities

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

Skills

Python

Pandas

NumPy

SciPy

Scikit-learn

TensorFlow

PyTorch

NLP

SQL

Data visualization

Flask

FastAPI

Docker

MLOps

Job description

Valiant Technologies LLC is seeking a Data Scientist in San Francisco to develop advanced analytical models, machine learning solutions, and predictive algorithms to solve business problems. The role emphasizes Python, NLP, statistics, and scalable model deployment.

The ideal candidate will deploy models to production, collaborate with data engineers and product teams, and communicate technical findings to stakeholders for data-driven decisions.