Job Description
At Vertex Dynamics, we are on a mission to redefine industry standards through data-driven innovation. We are seeking an exceptional Senior Data Scientist to join our elite team in New York City. In this role, you will own the full lifecycle of data science projects—from identifying business opportunities and defining success metrics to deploying cutting-edge machine learning models at scale. You will collaborate with cross-functional teams of engineers, product managers, and business leaders to solve complex challenges, optimize core processes, and unlock substantial business value. If you are passionate about leveraging big data and advanced analytics to drive tangible impact, we want to hear from you.
Responsibility
- Design, develop, and deploy advanced machine learning models and statistical analysis to solve critical business problems.
- Collaborate with product and engineering teams to identify high-impact opportunities for data science applications.
- Own the end-to-end data pipeline for model development, including data extraction, cleaning, feature engineering, training, validation, and deployment.
- Conduct rigorous A/B testing and experimentation to measure the impact of algorithmic changes and product features.
- Communicate complex quantitative findings and actionable insights to non-technical stakeholders and executive leadership.
- Mentor junior data scientists and contribute to the continuous improvement of our data science practices and codebase.
- Stay abreast of the latest research and technologies in machine learning, deep learning, and AI to drive continuous innovation.
Qualification
- Master's or Ph.D. in a quantitative field (Computer Science, Statistics, Mathematics, Physics, or related discipline).
- 5+ years of experience as a Data Scientist or Machine Learning Engineer in a production environment.
- Expert-level proficiency in Python and SQL; strong experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn).
- Deep understanding of statistical concepts (hypothesis testing, regression, Bayesian methods) and experimental design.
- Proven experience deploying models at scale using cloud platforms (AWS SageMaker, GCP Vertex AI, or Azure ML).
- Experience with big data technologies (Spark, Airflow, DBT) and data warehousing solutions.
- Strong business acumen and the ability to translate ambiguous business questions into concrete analytical tasks.