Data Scientist

As a Mid-Level Data Scientist, you will support efforts to design and implement advanced statistical and AI/ML solutions focused on extracting actionable insights, evaluating model performance, and leveraging semantic analysis techniques to enhance product safety decision-making. This role emphasizes innovation, efficiency, and interpretability in modern cloud data environments, contributing to strategic acceleration toward an AI-powered product safety Sentinel model that protects more consumers, faster, from more hazards. Key Responsibilities Insight Extraction & Semantic Analysis

• Apply semantic and vibe coding efficiencies to uncover patterns and thematic insights from structured and unstructured data.

• Translate complex data into clear, actionable narratives through data storytelling and visualization. Model Development & Evaluation

• Design, implement, and maintain AI approaches (such as product similarity) and predictive models (supervised and unsupervised) for anomaly detection, classification, regression, and pattern recognition.

• Conduct rigorous model evaluation using precision, recall, F1 score, AUC, and other performance metrics to ensure reliability and fairness. Innovation & Efficiency

• Demonstrate an innovative mindset by exploring emerging technologies, creative approaches, and novel methodologies to solve complex problems efficiently.
• Utilize modern efficiency tools and frameworks such as GitHub Copilot, automated pipelines, and CI/CD to streamline development and deployment.

• Optimize workflows for scalability in cloud environments (Azure). Collaboration & Communication

• Work collaboratively within Agile teams, contributing to iterative development, shared problem-solving, and continuous improvement.
• Communicate complex analytical findings clearly to both technical and non-technical stakeholders.
• Maintain documentation and leverage Git-based version control for collaborative development.

• Statistical & AI/ML Modeling: 3+ years developing statistical and AI/ML models using leading-edge tools and best practices.
• Predictive Analytics: 3+ years building regression, classification, NLP, and other statistical/ML models.
• Programming: 3+ years of hands-on experience with Python (Pandas, Scikit-learn, PyTorch/TensorFlow for deep learning).

• Cloud: 3+ years working in modern cloud environments (Azure); Hnds on Python coding, and/or R. Bottom line they should have coding experience.Background with any cloud service (AWS/Azure/Google Cloud Platform) matters and some experience working with LLMs aside from python coding. Certifications advantageous.

• SQL: 2+ years of experience with SQL for data manipulation and querying.
• Visualization: Proficiency in dashboard visualization tools such as Power BI or equivalent.
• Semantic Coding: Proven ability to integrate semantic coding techniques into ML workflows.

• Education: Bachelor’s, PhD, or equivalent professional experience in Data Science,Machine Learning, Computer Science, Mathematics, or related field. Preferred Qualifications

• Experience with Azure ML, Azure Synapse, or Azure Data Lake Storage.
• Familiarity with NLP pipelines and text classification applied to unstructured data.
• Experience in public sector or regulated environments.
• Azure certifications in data science or AI are a plus., * Strong oral and written communication skills for data storytelling with diverse audiences.
• Demonstrated experience with Git-based version control and collaborative development practices.
• Eagerness to learn and adopt new technologies, while actively contributing to team knowledge-sharing.
• Must be able to pass a Federal agency background check and obtain a government-issued. ID badge before starting work.