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Director of Data Science at Worth AI. Worth is seeking an experienced and visionary . Director of Data Science . to lead the development and deployment of machine learning and statistical modeling solutions that drive business impact across our organization. This individual will guide a team of data scientists and partner with cross-functional stakeholders to build scalable, production-grade models for both analytical and product applications.. The ideal candidate brings a strong foundation in predictive modeling, statistical analysis, and machine learning, with proven leadership experience in building data science teams and influencing strategic decisions. Expertise in areas such as NLP, computer vision, or reinforcement learning is highly desirable. This role requires exceptional communication skills and the ability to distill complex insights into clear, actionable recommendations for executive audiences.. Responsibilities. . Lead, mentor, and scale a high-performing team of data scientists while fostering a culture of innovation, collaboration, and continuous learning.. . Oversee the end-to-end development of machine learning models—design, training, validation, and deployment—within cloud-based production environments.. . Partner with product, engineering, and business teams to identify opportunities for data science solutions, define success metrics, and deliver measurable impact.. . Drive the integration of large-scale data systems and pipelines to power intelligent, adaptive models that reflect changing customer, market, and business dynamics.. . Ensure rigorous model monitoring, governance, and retraining protocols to maintain accuracy, fairness, and compliance.. . Communicate technical results and strategic insights clearly and persuasively to senior leadership and non-technical stakeholders.. . Champion the adoption of advanced analytics tools, frameworks, and best practices across the company.. . . Bachelor’s degree and 8+ years of professional experience, or Master’s degree and 6+ years, or PhD and 4+ years, in a quantitative field such as Computer Science, Statistics, Applied Mathematics, or Engineering.. . Proven leadership experience managing data science or machine learning teams in fast-paced, agile environments.. . Deep expertise in statistical modeling and machine learning techniques (e.g., regression, time series, clustering, ensemble methods, simulation, NLP, deep learning, etc.).. . Hands-on proficiency in Python and SQL; familiarity with R or other languages is a plus.. . Practical experience with ML libraries and frameworks such as Scikit-learn, TensorFlow, Keras, PyTorch, Statsmodels, NumPy, and SciPy.. Strong understanding of data architecture and MLOps practices in cloud environments such as AWS, Azure, or GCP.. . Excellent data storytelling and executive communication skills; confident in building and delivering compelling visual presentations (e.g., Tableau, PowerBI).. . Deep understanding of Agile methodologies such as Scrum or Kanban.. . . Company Location: United States.