Job Description
Are you ready to shape the future of Artificial Intelligence? Nebula Analytics is seeking a visionary Senior Data Scientist to join our dynamic team in San Francisco. We are a leading innovator in predictive modeling and big data solutions, dedicated to helping Fortune 500 companies leverage their data for competitive advantage.
In this role, you will bridge the gap between complex mathematical modeling and real-world business applications. You will lead high-impact projects, mentor junior data scientists, and collaborate closely with product and engineering teams to deploy state-of-the-art machine learning models.
Why join us?
We offer a competitive salary, comprehensive benefits, and a culture that prioritizes continuous learning and innovation. If you are passionate about turning data into actionable insights, we want to hear from you.
Responsibilities
- Design, develop, and deploy scalable machine learning models and statistical algorithms to solve complex business problems.
- Perform extensive exploratory data analysis (EDA) and feature engineering to prepare high-quality datasets for modeling.
- Collaborate with cross-functional teams including software engineers, product managers, and stakeholders to define project requirements and success metrics.
- Optimize and tune models for performance, accuracy, and scalability using cloud infrastructure (AWS/GCP).
- Communicate complex findings and model results to non-technical stakeholders through clear visualizations and reports.
- Stay current with the latest research in deep learning, NLP, and computer vision to integrate cutting-edge techniques into our stack.
- Conduct rigorous A/B testing and model validation to ensure reliability in production environments.
Qualifications
- Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Minimum of 5 years of professional experience in data science, machine learning, or statistical analysis.
- Strong proficiency in Python (pandas, NumPy, Scikit-learn) and experience with deep learning frameworks (PyTorch or TensorFlow).
- Expert knowledge of SQL and experience working with large-scale data warehouses (e.g., Snowflake, BigQuery).
- Proven track record of deploying end-to-end machine learning pipelines in production environments.
- Excellent communication skills, with the ability to translate technical jargon into business value.
- Familiarity with cloud computing platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).