Job Description
Are you ready to engineer the future of intelligence?
Nexus AI Solutions is on the hunt for a visionary Senior Data Scientist to join our elite engineering team in San Francisco. We are not just building models; we are architecting the next generation of cognitive systems that redefine how businesses interact with data. If you have a passion for turning raw information into strategic gold and thrive in a fast-paced, high-impact environment, we want to meet you.
As a key member of our data science division, you will bridge the gap between complex statistical theory and real-world product applications. You will work closely with product managers, engineers, and stakeholders to solve ambiguous problems using advanced machine learning techniques. We offer a competitive compensation package, comprehensive benefits, and the opportunity to work with state-of-the-art technology on projects that matter.
Why Nexus AI?
- Work on cutting-edge AI/ML projects.
- Competitive salary and equity package.
- Flexible remote and hybrid work options.
- Continuous learning and development budget.
Join us in shaping the future of analytics.
Responsibilities
- Model Development & Deployment: Design, train, and deploy advanced machine learning models and deep learning algorithms to solve complex business problems.
- Data Strategy: Own the end-to-end data science lifecycle, from data ingestion and cleaning to feature engineering and model validation.
- Collaboration: Partner with cross-functional teams (Product, Engineering, Design) to translate business requirements into technical data science solutions.
- Performance Optimization: Continuously monitor, evaluate, and optimize model performance to ensure scalability, accuracy, and speed.
- Research: Stay at the forefront of industry trends, research new methodologies, and implement best practices in AI/ML.
- Mentorship: Guide junior data scientists and engineers, fostering a culture of technical excellence and innovation.
- Visualization: Create compelling data visualizations and reports to communicate insights effectively to non-technical stakeholders.
Qualifications
- Education: Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Technical Skills: Strong proficiency in Python (PyTorch, TensorFlow, Scikit-learn) and SQL.
- Experience: Minimum of 5+ years of professional experience in data science, machine learning, or a related analytical role.
- Big Data: Experience with distributed computing frameworks such as Spark, Hadoop, or cloud-based data warehouses (e.g., AWS Redshift, Google BigQuery).
- Communication: Exceptional ability to translate complex data findings into clear, actionable business insights for diverse audiences.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and derive creative, data-driven solutions.
- Portfolio: A strong portfolio of projects demonstrating applied machine learning skills and impact.