Agile Programming Methodologies, Analysis Skills, Artificial Intelligence (AI), Background Investigation, Best Practices, Cloud Computing, Communication Skills, Computer Science, Consumer Protection, Continuous Deployment/Delivery, Continuous Improvement, Continuous Integration, Data Science, Deep Learning, Documentation, Emerging Technology, Federal Government, Git, GitHub, Government, Machine Learning, Mathematics, Microsoft Windows Azure, Natural Language Processing (NLP), Pattern Matching, Performance Metrics, Performance Modeling, Power BI, Predictive Modeling, Presentation/Verbal Skills, Problem Solving Skills, Product Safety, Python Programming/Scripting Language, Reporting Dashboards, SQL (Structured Query Language), Source Code/Configuration Management (SCM), Statistical Modeling, Storytelling, Structured Data, Team Player, Unstructured Data, Writing Skills
Role: Mid-Level Data Scientist
Location: Fully Remote
Duration: Full Time
Job Description
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 predictivemodels (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.
Required Qualifications
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 hands-on experience with Python (Pandas, Scikit-learn, PyTorch/TensorFlow for deep learning).
Cloud: 3+ years working in modern cloud environments (Azure);
Certifications advantageous.
SQL: 2+ years 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: Bachelors, 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.
Other Qualifications
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 prior to starting work.