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Information Technology 🏢 Full Time ⭐️ Verified

Senior Data Scientist

Nexus AI Analytics
San Francisco
Salary Estimate
USD 160.000 – USD 210.000
Live Update
10 Mei 2026
Deadline
10 Mei 2027

Job Description

Are you ready to shape the future of machine learning? Nexus AI Analytics is seeking a Senior Data Scientist to join our elite engineering team in the heart of San Francisco. You will leverage cutting-edge deep learning frameworks to solve complex business challenges and drive product innovation for global clients.

We offer a collaborative, remote-friendly culture, top-tier compensation, and the opportunity to work with vast, proprietary datasets. If you are passionate about building scalable, production-grade models, we want to hear from you.

Responsibilities

  • Design and implement end-to-end machine learning pipelines for predictive analytics.
  • Collaborate with cross-functional teams to identify and translate business problems into data-driven solutions.
  • Conduct advanced statistical analysis to derive actionable insights from complex datasets.
  • Deploy models into production environments utilizing MLOps best practices.
  • Mentor junior data scientists and contribute to engineering excellence via code reviews.
  • Stay at the forefront of AI research and introduce new methodologies to our tech stack.

Qualifications

  • Master's or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • 5+ years of professional experience in data science, machine learning, or statistical modeling.
  • Expert-level proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
  • Strong knowledge of SQL, cloud-based data warehouses (Snowflake, BigQuery), and distributed computing (Spark).
  • Experience with containerization and orchestration (Docker, Kubernetes).
  • Excellent communication skills with the ability to explain complex technical concepts to non-technical stakeholders.

Required Skills

Python Machine Learning PyTorch SQL MLOps Statistics Deep Learning Cloud Computing

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