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Lead Data Scientist - AI & Machine Learning

QuantumCore AI
San Francisco
Salary Estimate
USD 160.000 – USD 210.000
Latest
Live Update
24 Mei 2026
Deadline
24 Mei 2027

Job Description

Join the Future of Intelligence at QuantumCore AI

We are seeking a visionary Lead Data Scientist to spearhead our advanced AI research initiatives. As a key player in our R&D division, you will bridge the gap between complex mathematical models and scalable production software. You will work with a world-class team to develop cutting-edge algorithms that power our next-generation predictive analytics platform.

Why Join Us?

  • Competitive equity and salary package.
  • Flexible remote-first policy with a San Francisco hub.
  • Access to state-of-the-art hardware and cloud infrastructure.

If you are passionate about solving hard problems and want to have a tangible impact on the industry, we want to hear from you.

Responsibilities

  • Design, develop, and deploy state-of-the-art machine learning models, including deep learning and NLP architectures.
  • Lead the end-to-end data science lifecycle, from data acquisition and cleaning to model training, validation, and production deployment.
  • Collaborate with cross-functional teams of engineers, product managers, and domain experts to define technical requirements and business solutions.
  • Perform rigorous statistical analysis and A/B testing to validate model performance and drive product optimization.
  • Mentor junior data scientists and engineers, fostering a culture of technical excellence and continuous learning.
  • Stay abreast of the latest research in the field and implement innovative techniques to improve system efficiency.

Qualifications

  • Master’s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
  • Minimum of 5 years of professional experience in data science, machine learning, or AI engineering.
  • Strong proficiency in programming languages such as Python (PyTorch, TensorFlow, Scikit-learn) and SQL.
  • Proven experience with big data technologies (Spark, Hadoop) and cloud platforms (AWS, GCP, or Azure).
  • Deep understanding of statistical modeling, data mining, and feature engineering techniques.
  • Excellent communication skills with the ability to translate complex technical concepts into actionable business insights.

Required Skills

Python TensorFlow PyTorch SQL Machine Learning Deep Learning Statistics AWS Spark Data Mining MLOps Scikit-learn

Ready to Take on This Challenge?

Make sure your resume is ready. Submit your application now before the deadline.

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