Job Description
Are you ready to shape the future of Artificial Intelligence?
Nexus Data Labs is a premier technology firm driving innovation in predictive analytics and machine learning. We are looking for a highly skilled Senior Data Scientist to join our elite R&D team. In this role, you will transform raw data into actionable business intelligence, optimizing our core algorithms to solve complex challenges.
You will work in a collaborative environment with world-class engineers and product managers. If you are passionate about pushing the boundaries of what's possible with data and have a track record of delivering scalable solutions, we want to hear from you.
Responsibilities
- Model Development: Design, train, and deploy state-of-the-art machine learning models, including deep learning and NLP solutions.
- Data Strategy: Lead the end-to-end data pipeline architecture, ensuring scalability, efficiency, and data integrity.
- Cross-Functional Collaboration: Partner with product and engineering teams to translate business requirements into technical data solutions.
- Feature Engineering: Identify, extract, and refine features from vast datasets to improve model performance and accuracy.
- Performance Analysis: Monitor model performance in production, conduct A/B testing, and iterate on algorithms to drive continuous improvement.
- Research: Stay abreast of the latest industry trends and academic research to integrate cutting-edge techniques into our tech stack.
- Stakeholder Communication: Present complex technical findings and model insights to non-technical stakeholders in a clear, compelling manner.
Qualifications
- Education: Master’s or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
- Experience: Minimum of 5+ years of professional experience in data science or machine learning engineering.
- Programming: Strong proficiency in Python (PyTorch, TensorFlow, Scikit-learn) and SQL.
- Big Data: Experience with distributed computing frameworks such as Apache Spark or Hadoop.
- Mathematical Proficiency: Solid foundation in statistics, linear algebra, and calculus.
- Communication: Exceptional ability to communicate complex technical concepts to diverse audiences.
- Tools: Familiarity with cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).