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Data Science 🏢 Full Time ⭐️ Verified

Senior Data Scientist

NovaMetrics AI
San Francisco, CA
Salary Estimate
USD 130.000 – USD 180.000
Posting Time
7 Mei 2026
Deadline
7 Mei 2027

Job description

NovaMetrics AI is seeking a Senior Data Scientist to join our fast-growing data team in San Francisco. You will translate complex data into measurable business impact, build scalable models, and collaborate with product, engineering, and research partners.

We champion a culture of curiosity, clean code, and data-driven decision making. You will own end-to-end machine learning projects, from problem framing to deployment and monitoring, ensuring robust performance in production.

Responsibility

  • Design, implement, and optimize production-ready ML models that drive key business metrics.
  • Collaborate with product and engineering teams to translate business problems into data science solutions.
  • Prepare and analyze large datasets, perform feature engineering, and validate model performance.
  • Own model lifecycle, including training, validation, deployment, monitoring, and maintenance.
  • Prototype innovative analytical solutions and contribute to data strategy and governance.
  • Communicate findings to stakeholders with clear visualizations and actionable insights.

Qualification

  • MS in Computer Science, Statistics, Applied Math, or related field; PhD preferred.
  • 5+ years of experience in data science or ML engineering.
  • Proficiency in Python and libraries (scikit-learn, pandas, NumPy); strong SQL skills.
  • Experience with ML frameworks (TensorFlow, PyTorch) and model deployment (Docker, Kubernetes).
  • Experience with cloud platforms (AWS, GCP, or Azure) and data pipelines (Airflow, Spark).
  • Strong problem-solving, communication, and collaboration skills; ability to translate complex concepts for non-technical audiences.
  • Track record of delivering impact on product or business metrics; publication or patent a plus.
  • Familiarity with MLOps and model monitoring, security, and compliance considerations.

Required Skills

Python SQL machine learning data visualization NumPy pandas scikit-learn TensorFlow PyTorch Spark Docker Kubernetes AWS GCP data wrangling feature engineering experimentation

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