Job Description
Are you ready to shape the future of Artificial Intelligence?
Nexus AI Solutions is a pioneering tech firm dedicated to transforming complex data into actionable intelligence. We are looking for a visionary Senior Data Scientist to join our elite R&D team in San Francisco. In this role, you will architect predictive models that drive our core product strategy and define the next generation of machine learning applications.
We offer a competitive compensation package, equity opportunities, and a collaborative environment where your code impacts millions of users globally. If you are passionate about Deep Learning, NLP, and scalable architecture, we want to meet you.
Responsibility
- Model Development: Design, train, and deploy advanced machine learning and deep learning models using Python, PyTorch, and TensorFlow.
- Data Strategy: Lead the end-to-end data pipeline process, from data ingestion and cleaning to feature engineering and model evaluation.
- Cross-Functional Collaboration: Partner with product managers and software engineers to translate business requirements into technical solutions.
- Research & Innovation: Stay at the forefront of industry trends, researching novel algorithms to improve model accuracy and efficiency.
- Performance Optimization: Optimize existing models for speed, scalability, and low latency in production environments.
- Visualization: Create compelling data visualizations and dashboards to communicate complex insights to non-technical stakeholders.
Qualification
- Education: Master’s or PhD degree in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Experience: 5+ years of professional experience in data science, machine learning, or a similar analytical role.
- Technical Skills: Proficiency in Python (Pandas, NumPy, Scikit-learn) and SQL. Experience with cloud platforms (AWS/GCP/Azure) is highly preferred.
- Frameworks: Strong understanding of deep learning frameworks (TensorFlow, Keras) and experience with NLP or Computer Vision is a plus.
- Problem Solving: Demonstrated ability to tackle ambiguous problems and derive statistical insights from unstructured data.
- Communication: Excellent written and verbal communication skills, with the ability to present technical concepts to diverse audiences.