Job Description
Join Nexus Analytics, a trailblazing data intelligence firm, as we revolutionize how Fortune 500 companies leverage data for strategic advantage. We're seeking a visionary Senior Data Scientist to architect cutting-edge analytics solutions that drive measurable business impact. In this role, you'll collaborate with cross-functional teams to transform complex datasets into actionable insights, directly influencing product development and revenue optimization. Our dynamic environment fosters innovation through hackathons, research stipends, and access to AWS/GCP enterprise infrastructure.
Located in the heart of San Francisco's tech corridor, we offer hybrid work flexibility, comprehensive health benefits, and equity participation. Your work will power decisions impacting millions of users across fintech, healthcare, and e-commerce verticals. If you're passionate about solving ambiguous problems with elegant data solutions, we invite you to apply.
Responsibilities
- Design and implement end-to-end machine learning pipelines for predictive modeling and anomaly detection
- Lead A/B testing frameworks and causal inference projects to quantify product impact
- Develop scalable data visualizations using Tableau and custom D3.js dashboards
- Mentor junior analysts through code reviews and technical workshops
- Present findings to C-suite executives with clear business narratives
- Optimize data warehouse architecture for query efficiency and cost reduction
- Research emerging ML techniques (e.g., NLP, graph analytics) for pilot implementations
Qualifications
- MS/PhD in Statistics, Computer Science, or quantitative field with 5+ years experience
- Expert proficiency in Python (scikit-learn, PyTorch) and SQL (PostgreSQL, BigQuery)
- Proven track record deploying production ML systems at scale
- Strong statistical foundation with experimental design expertise
- Experience with cloud platforms (AWS SageMaker/GCP Vertex AI)
- Advanced data storytelling skills with executive presentation experience
- Published research in top-tier ML/DS conferences or journals preferred
- Portfolio demonstrating 3+ end-to-end data science projects