Data Scientist Supervisor # 26-28558

• The Data Science Supervisor has experience working directly with client-centric relational databases and managing personnel, * They possess strong technical knowledge, advise on complex database buildouts, and comfortably lead projects where the strategic path forward is ambiguous.
• They are seasoned facilitators with a customer service mindset, functioning as both a technical and supervisory lead within a collaborative team structure while reviewing the work products of data scientists and analysts alongside engineering. They serve as the team’s Lead for ETL, backend pipelines, and cloud environments (such as Databricks).
• They act as the Primary Lead for technical and code-level documentation, and Co-Lead for system documentation, API layouts, and ETL business logic.
• Additionally, they function as the Technical Lead for data security implementation and the Lead for Quality Assurance, overseeing unit testing and code integrity protocols.
• Additionally, the Data Science Supervisor will actively engage in team Agile/Scrum workflows, consulting on technical feasibility and backend effort, supporting deployment and change management, and directly driving sprint planning and daily stand-ups by managing blockers and committing to technical deliverables.

Data Science, Data Science, People Management, Relational Databases (RDBMS), Team Player, Cloud Computing, Customer Support/Service, Database Extract Transform and Load (ETL), Data Analysis, Product Reviews, * Six (6) years of experience, including three (3) years supervising a team of data science professionals serving as subject matter experts and coordinating and overseeing complex data science projects to support program, policy, and operational decision-making

• The supervisor possesses deep expertise in machine learning techniques (supervised and unsupervised learning, including regression, classification, clustering, and dimensionality reduction), statistical analysis, and hypothesis testing.
• They bring hands-on proficiency in data manipulation (Pandas, NumPy, Scikit-learn), big data frameworks (Apache Spark, Hadoop), Python, R, and SQL, alongside experience deploying models using Docker, Flask, or cloud platforms (AWS, Azure).
• The Data Science Supervisor will have advanced data visualization skills in Tableau, Power BI, Matplotlib, Seaborn or similar, as it is a foundational knowledge of data engineering practices, pipeline design, and data warehousing., * A Master’s degree from an accredited college or university in applied research, such as Data Science, Machine Learning, Mathematics, Statistics, Business Analytics, Psychology, or Public Health, may be substituted for two (2) years toward the minimum years of qualifying experience.