Sr Data Scientist - Remote

Primary Responsibilities

• Design, develop, and deploy AI-powered solutions to address complex business challenges, collaborating with research, engineering, and product teams to translate cutting-edge AI advancements into scalable, production-ready capabilities.
• Analyze large, complex, and diverse datasets to identify trends, anomalies, hidden relationships, and previously undiscovered insights across the enterprise.
• Develop predictive, prescriptive, and optimization models to improve business performance and operational effectiveness using machine learning, deep learning, NLP, and generative AI capabilities.
• Evaluate emerging AI/ML trends to inform solution design, strategic innovation, and continuous improvement across enterprise applications.
• Uphold ethical AI principles by embedding fairness, transparency, and accountability throughout the model development lifecycle.
• Use enterprise-approved AI tools to streamline workflows, automate tasks, and drive continuous improvement.
• Partner with business, product, operations, and technology teams to translate complex analytical findings into clear business recommendations and executive-level insights.
• Design and implement scalable analytical frameworks, reusable models, and decision-support solutions.
• Mentor junior data scientists and analysts on analytical techniques, experimental design, and model development.

Required Qualifications

• 5+ years of experience in Data Science, Advanced Analytics, Machine Learning, or AI-related roles.
• 3+ years of experience programming in Python, R, or SQL for data modeling and analysis.
• 3+ years of experience with machine learning frameworks (e.g., Scikit-learn, TensorFlow, PyTorch, XGBoost).
• 2+ years of experience working with large-scale structured and unstructured enterprise datasets.
• 2+ years of experience with experimental design, hypothesis testing, optimization, and predictive modeling.

Preferred Qualifications

• Experience applying Generative AI, Large Language Models (LLMs), Agentic AI, or advanced AI techniques to business problems.
• Knowledge of cloud-based analytics platforms and modern data ecosystems.
• Experience building recommendation engines, pattern detection frameworks, anomaly detection models, or intelligent automation solutions.
• Experience operating in highly regulated, data-intensive enterprise environments.