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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
Latest
Live Update
1 Juni 2026
Deadline
1 Jun 2027

Job Description

Are you ready to shape the future of machine learning? Nexus AI is seeking a visionary Senior Data Scientist to join our elite core engineering team. You will work at the intersection of deep learning and predictive analytics to solve complex, real-world problems for global enterprises. We offer a high-impact, collaborative environment where your models directly influence product strategy and customer experience.

We prioritize innovation, technical excellence, and a data-driven culture. If you are passionate about scalable AI and pushing the boundaries of what is possible, we want to hear from you.

Responsibilities

  • Design, develop, and deploy end-to-end machine learning pipelines to solve critical business challenges.
  • Collaborate with cross-functional product and engineering teams to identify high-value data opportunities.
  • Build and optimize statistical models, including regression, clustering, and neural network architectures.
  • Perform advanced exploratory data analysis to uncover hidden patterns and actionable business insights.
  • Mentor junior data scientists and promote best practices in code quality and model experimentation.
  • Communicate findings and technical roadmaps to senior stakeholders through compelling data storytelling.
  • Stay at the forefront of AI research and integrate cutting-edge algorithms into our proprietary platform.

Qualifications

  • Master’s or Ph.D. in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • 5+ years of professional experience in data science, predictive modeling, or machine learning.
  • Expert-level proficiency in Python and deep learning frameworks (PyTorch or TensorFlow).
  • Strong knowledge of SQL, NoSQL databases, and large-scale data processing tools like Spark.
  • Proven track record of deploying models into production environments (CI/CD, Docker, Kubernetes).
  • Deep understanding of statistical inference, optimization techniques, and feature engineering.
  • Excellent communication skills with the ability to bridge the gap between complex mathematics and business strategy.

Required Skills

Python Machine Learning Deep Learning SQL PyTorch TensorFlow Statistics Data Visualization Cloud Computing

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