Job Description
Nexus AI Systems is at the forefront of predictive analytics and machine learning innovation. We are looking for a Senior Data Scientist to join our elite engineering team in San Francisco. In this role, you will architect scalable models, derive actionable insights from complex datasets, and drive decision-making for our global product suite.
We value technical excellence, intellectual curiosity, and the ability to turn ambiguity into high-impact business solutions. If you are passionate about building robust machine learning pipelines and thriving in a fast-paced, collaborative environment, we want to hear from you.
Responsibilities
- Design, develop, and deploy production-grade machine learning models to solve complex business problems.
- Collaborate with cross-functional product and engineering teams to identify data-driven opportunities.
- Perform deep-dive exploratory data analysis to uncover hidden patterns and trends in massive datasets.
- Optimize and scale existing algorithmic pipelines for performance and efficiency.
- Mentor junior data scientists and contribute to architectural reviews and technical documentation.
- Communicate complex statistical concepts to non-technical stakeholders through compelling data storytelling.
- Stay abreast of state-of-the-art research in ML and AI, applying innovative techniques to internal projects.
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 engineering.
- Expert-level proficiency in Python and libraries such as Scikit-Learn, PyTorch, or TensorFlow.
- Deep experience with SQL and NoSQL databases for large-scale data manipulation.
- Proven track record of deploying models into production environments (AWS, GCP, or Azure).
- Strong understanding of statistical modeling, hypothesis testing, and experimental design.
- Excellent verbal and written communication skills with the ability to influence technical and non-technical audiences.