Job Description
At NexusAI, we are at the forefront of revolutionizing how businesses leverage artificial intelligence. We are seeking a visionary Senior Data Scientist to join our dynamic team in San Francisco. In this role, you will bridge the gap between complex data and strategic product decisions, driving tangible business impact through state-of-the-art machine learning models and analytical rigor.
You will collaborate closely with product managers, engineers, and executive stakeholders to identify high-impact opportunities, design rigorous experiments, and deploy scalable models into production. If you are passionate about turning data into actionable insights and thrive in a fast-paced, innovative environment, we want to hear from you.
Responsibility
- Lead the end-to-end development of machine learning models, from problem formulation and data exploration to deployment and monitoring in a production environment.
- Design and analyze A/B tests and causal inference studies to optimize product features and drive user growth.
- Collaborate with cross-functional teams (Engineering, Product, Marketing) to identify data-driven opportunities and translate business questions into analytical frameworks.
- Mentor junior data scientists and analysts, fostering a culture of technical excellence and curiosity.
- Develop and maintain scalable data pipelines and feature engineering processes in partnership with Data Engineering.
- Communicate complex quantitative findings and business recommendations clearly and effectively to non-technical stakeholders and C-level executives.
- Stay abreast of the latest developments in machine learning, deep learning, and AI research to continuously improve our toolkit and methodologies.
Qualification
- Masters or PhD in Computer Science, Statistics, Mathematics, or a related quantitative field.
- 5+ years of industry experience in a Data Science or Machine Learning role, with a proven track record of delivering impactful models.
- Deep proficiency in Python and SQL; experience with R, Scala, or Julia is a plus.
- Expertise in modern ML frameworks (TensorFlow, PyTorch, Scikit-learn) and statistical methods (regression, hypothesis testing, Bayesian analysis).
- Strong experience with cloud-based MLOps platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
- Excellent problem-solving skills and the ability to work independently in a highly ambiguous environment.
- Outstanding verbal and written communication skills, with a demonstrated ability to influence product strategy through data.