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Data Science 🏢 Full Time ⭐️ Verified

Senior Data Scientist

NovaData Labs
San Francisco, CA
Salary Estimate
USD 150.000 – USD 190.000
Posting Time
6 Mei 2026
Deadline
6 Mei 2027

Job description

NovaData Labs is seeking a Senior Data Scientist to join our growing Data Science Studio in San Francisco. You will shape data product strategy, build end-to-end ML models, and deploy them into production alongside a cross-functional team.

As a core member of the data science team, you will partner with product, engineering, and design to translate complex business problems into scalable machine learning solutions that drive measurable impact for our clients and internal stakeholders.

We offer a collaborative culture, competitive compensation, equity options, and a strong focus on learning and career growth. This is a hands-on, high-visibility role with room to influence data strategy across the organization.

Responsibility

  • Lead end-to-end data science projects from problem framing to production deployment and monitoring.
  • Design, implement, and iterate machine learning models using Python and modern frameworks (scikit-learn, TensorFlow, PyTorch).
  • Build robust data pipelines and feature stores in collaboration with data engineering.
  • Experiment, validate, and communicate model results; design A/B tests and track business impact.
  • Collaborate with product and engineering to deploy models into production on cloud platforms and ML Ops tooling.
  • Create dashboards, reports, and data visualizations to translate insights for non-technical stakeholders.
  • Mentor junior data scientists, contribute to code reviews, and promote ML best practices.

Qualification

  • Master's or PhD in Computer Science, Statistics, Applied Math, or equivalent; 5+ years of industry experience in data science.
  • Proficiency in Python and SQL with strong experience in ML libraries (scikit-learn, TensorFlow, PyTorch).
  • Hands-on experience with cloud platforms (AWS, GCP, or Azure) and MLOps tooling (Kubeflow, Airflow, Docker, Kubernetes).
  • Strong SQL and data modeling skills; experience with Spark, BigQuery, or similar big data engines.
  • Proven track record delivering production ML systems with measurable business impact.
  • Excellent communication and collaborative skills; ability to explain complex concepts to non-technical audiences.
  • Experience with experimentation design, monitoring, and model governance.

Required Skills

Python R SQL machine learning deep learning TensorFlow PyTorch scikit-learn Spark BigQuery AWS GCP Azure Docker Kubernetes MLOps

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