Job Description
Are you ready to engineer the future of intelligence?
Nebula AI is on a mission to revolutionize how businesses leverage predictive analytics. We are seeking a highly skilled and innovative Senior Data Scientist to join our San Francisco headquarters. In this role, you will be the architect of our next-generation data models, transforming terabytes of raw information into strategic assets that drive growth.
What You Will Do:
• Design, train, and deploy advanced machine learning algorithms.
• Lead data exploration and feature engineering to ensure high-quality inputs for our models.
• Collaborate with cross-functional product teams to define data requirements and success metrics.
• Translate complex data findings into compelling visualizations and actionable business insights for stakeholders.
• Optimize data processing pipelines and infrastructure for speed and scalability.
Who We Are Looking For:
• A Master’s or PhD in Computer Science, Statistics, or a related quantitative field.
• Proven experience (5+ years) in applying statistical methods and machine learning to real-world problems.
• Deep expertise in Python (Pandas, Scikit-learn) and SQL.
• Familiarity with deep learning frameworks (TensorFlow, PyTorch) is highly desirable.
• Strong communication skills with the ability to explain technical concepts to non-technical audiences.
Why Apply?
• Competitive base salary ($140k - $180k) plus equity.
• Comprehensive health, dental, and vision coverage.
• Flexible working hours and remote-first culture.
• Continuous education stipend for conferences and courses.
Nebula AI is on a mission to revolutionize how businesses leverage predictive analytics. We are seeking a highly skilled and innovative Senior Data Scientist to join our San Francisco headquarters. In this role, you will be the architect of our next-generation data models, transforming terabytes of raw information into strategic assets that drive growth.
What You Will Do:
• Design, train, and deploy advanced machine learning algorithms.
• Lead data exploration and feature engineering to ensure high-quality inputs for our models.
• Collaborate with cross-functional product teams to define data requirements and success metrics.
• Translate complex data findings into compelling visualizations and actionable business insights for stakeholders.
• Optimize data processing pipelines and infrastructure for speed and scalability.
Who We Are Looking For:
• A Master’s or PhD in Computer Science, Statistics, or a related quantitative field.
• Proven experience (5+ years) in applying statistical methods and machine learning to real-world problems.
• Deep expertise in Python (Pandas, Scikit-learn) and SQL.
• Familiarity with deep learning frameworks (TensorFlow, PyTorch) is highly desirable.
• Strong communication skills with the ability to explain technical concepts to non-technical audiences.
Why Apply?
• Competitive base salary ($140k - $180k) plus equity.
• Comprehensive health, dental, and vision coverage.
• Flexible working hours and remote-first culture.
• Continuous education stipend for conferences and courses.
Responsibilities
• Design and implement scalable machine learning algorithms to drive business insights.
• Conduct exploratory data analysis (EDA) to uncover hidden patterns and trends.
• Collaborate with engineering teams to deploy models into production environments.
• Communicate complex data findings to non-technical stakeholders through clear visualizations and reports.
• Optimize data pipelines and infrastructure for maximum efficiency and scalability.
• Conduct exploratory data analysis (EDA) to uncover hidden patterns and trends.
• Collaborate with engineering teams to deploy models into production environments.
• Communicate complex data findings to non-technical stakeholders through clear visualizations and reports.
• Optimize data pipelines and infrastructure for maximum efficiency and scalability.
Qualifications
• Master’s or PhD in Computer Science, Statistics, Mathematics, or a related field.
• 5+ years of professional experience in Data Science or Machine Learning.
• Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
• Experience with deep learning frameworks (TensorFlow, PyTorch) is a plus.
• Strong understanding of statistical inference and experimental design.
• Excellent problem-solving skills and ability to work in a fast-paced Agile environment.
• 5+ years of professional experience in Data Science or Machine Learning.
• Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL.
• Experience with deep learning frameworks (TensorFlow, PyTorch) is a plus.
• Strong understanding of statistical inference and experimental design.
• Excellent problem-solving skills and ability to work in a fast-paced Agile environment.