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Senior Data Scientist - Machine Learning - San Francisco, CA

Nexus Data Intelligence
San Francisco
Salary Estimate
USD 140.000 – USD 180.000
Live Update
10 Mei 2026
Deadline
10 Mei 2027

Job Description

Nexus Data Intelligence is at the forefront of leveraging artificial intelligence to solve complex business challenges. We are looking for a visionary Senior Data Scientist to join our elite analytics team in San Francisco. In this pivotal role, you will design, implement, and deploy scalable machine learning models that drive strategic decision-making across our global operations. You will work closely with cross-functional teams to transform vast, complex datasets into actionable business insights that directly impact revenue and operational efficiency.

Why Join Us?

• Work with state-of-the-art technology and a team of industry experts.

• Competitive compensation package and comprehensive benefits.

• Hybrid work model with a focus on innovation and collaboration.

Responsibilities

  • Design, develop, and deploy robust machine learning models and statistical algorithms.
  • Perform extensive exploratory data analysis (EDA) and feature engineering to drive model accuracy.
  • Collaborate with product managers and engineers to translate business requirements into technical solutions.
  • Communicate complex data findings and model performance to non-technical stakeholders through clear visualization and storytelling.
  • Optimize data pipelines and ensure scalability of data infrastructure.
  • Stay abreast of the latest research in deep learning and data science to continuously improve our competitive edge.

Qualifications

  • Ph.D. or Master’s degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Minimum of 5+ years of professional experience in Data Science, Analytics, or Machine Learning Engineering.
  • Strong proficiency in Python (Pandas, NumPy, Scikit-learn, PyTorch) and SQL.
  • Proven experience with big data technologies (Spark, Hadoop) and cloud platforms (AWS, GCP, or Azure).
  • Experience with MLOps practices, model deployment, and CI/CD pipelines.

Required Skills

Python Machine Learning SQL TensorFlow PyTorch Data Analysis Statistics AWS GCP Communication Leadership

Ready to Take on This Challenge?

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