Job description
Join NexGen Analytics as a Senior Data Scientist in the heart of San Francisco and elevate your career at an innovative, world-class data-driven organization. You will leverage state-of-the-art machine learning and advanced analytics to drive impactful, real-world business solutions. Collaborate with top-tier talent, work on cutting-edge projects, and make a measurable difference by uncovering insights in complex data sets. If you’re passionate about data science and thrive on challenges, we want to hear from you.
Responsibility
- Design, develop, and deploy advanced machine learning models for large-scale business challenges.
- Collaborate with cross-functional teams to define data-driven strategies and deliver actionable insights.
- Translate business questions into analytical frameworks and deliver clear, impactful results to stakeholders.
- Lead the collection, cleansing, and preprocessing of complex and diverse data sets.
- Mentor junior data scientists and promote a culture of continuous learning and technical excellence.
- Continuously monitor, evaluate, and improve the performance of deployed models and solutions.
- Communicate findings and recommendations through compelling data visualizations and presentations.
- Stay up to date with the latest industry best practices, technologies, and research.
Qualification
- Master’s degree or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
- 5+ years’ experience in data science or machine learning roles, ideally in a fast-paced environment.
- Proficiency in Python, R, SQL, and modern ML frameworks (e.g., TensorFlow, PyTorch, Scikit-learn).
- Strong foundation in statistical modeling, data wrangling, and algorithm development.
- Demonstrated ability to build and deploy production-grade models using cloud platforms (AWS, GCP, or Azure).
- Excellent problem-solving skills and a keen analytical mindset.
- Proven ability to communicate complex technical concepts to non-technical audiences.
- Experience mentoring and leading data science teams is highly desirable.