Data Scientist

Robotics Technologies; San Francisco (CA); On-site; USD 93,000 - 133,000; Full time

Job summary

Robotics Technologies in San Francisco, CA is hiring an on-site Data Scientist to build predictive analytics, NLP solutions, and production-ready machine learning models.

You will work across the full model lifecycle, from exploratory analysis and model development to deployment, monitoring, and continuous improvement, collaborating with data engineers, product teams, and business stakeholders to align modeling work with real-world needs.

Qualifications

• Strong Python programming experience.
• Proficient with Pandas, NumPy, SciPy.
• Experience with scikit-learn and ML algorithms.
• Experience with TensorFlow or PyTorch.
• Strong understanding of statistics and probability.
• Experience with NLP and text analytics.
• Knowledge of SQL and database management.
• Experience with data visualization using Matplotlib or Plotly.
• Understanding of feature engineering and model optimization.
• Experience with model deployment using Flask or FastAPI.
• Familiarity with Git, Docker, and ML development workflows.

Responsibilities

• Develop and implement machine learning models for predictive analytics.
• Conduct exploratory data analysis and uncover patterns in complex datasets.
• Create classification, regression, and clustering models.
• Develop NLP solutions for text processing and sentiment analysis.
• Apply statistical techniques that support data-driven decision-making.
• Perform feature engineering, model selection, and hyperparameter tuning.
• Build model evaluation frameworks to measure accuracy and performance.
• Deploy machine learning models into production environments.
• Monitor model performance and implement improvements over time.
• Present analytical findings and technical recommendations to stakeholders.

Skills

Python

Pandas

NumPy

SciPy

scikit-learn

TensorFlow

PyTorch

NLP

Statistics

Probability

SQL

Data viz

Matplotlib

Plotly

Flask

FastAPI

Git

Docker

ML workflows

Tools

Flask

FastAPI

Git

Docker

Job description

Robotics Technologies is hiring an on-site Data Scientist in San Francisco, CA to build predictive analytics, NLP solutions, and production-ready machine learning models. In this role, you will work across the full model lifecycle, from exploratory analysis and model development to deployment, monitoring, and continuous improvement.

What you’ll build and improve

• Develop and implement machine learning models for predictive analytics
• Conduct exploratory data analysis and uncover patterns in complex datasets
• Create classification, regression, and clustering models
• Develop NLP solutions for text processing and sentiment analysis
• Apply statistical techniques that support data-driven decision-making
• Perform feature engineering, model selection, and hyperparameter tuning
• Build model evaluation frameworks to measure accuracy and performance

Production-focused work

• Work with large datasets using Python and distributed computing tools
• Deploy machine learning models into production environments
• Monitor model performance and implement improvements over time
• Present analytical findings and technical recommendations to stakeholders

Collaboration and communication

You will collaborate with data engineers, product teams, and business stakeholders to align modeling work with real-world needs.

Required skills

• Strong Python programming experience
• Hands-on experience with Pandas, NumPy, and SciPy
• Expertise in scikit-learn and machine learning algorithms
• Experience with TensorFlow or PyTorch
• Strong understanding of statistics and probability
• Experience with NLP and text analytics
• Knowledge of SQL and database management
• Experience with data visualization using Matplotlib or Plotly
• Understanding of feature engineering and model optimization
• Experience with model deployment using Flask or FastAPI
• Familiarity with Git, Docker, and ML development workflows

Helpful experience

• Experience with Generative AI and Large Language Models (LLMs)
• Knowledge of RAG and vector databases
• Experience with MLflow and model lifecycle management
• Familiarity with AWS SageMaker or Azure Machine Learning
• Knowledge of Apache Spark and distributed data processing
• Understanding of MLOps and model monitoring

Compensation: USD 82 - 82 per hour.