Data Scientist

Job Summary:

The Data Analytical Specialist/Scientist will lead and execute advanced analytics and machine learning initiatives to support evidence-based decision-making within government ministries. This role involves developing statistical models, managing data pipelines, and delivering actionable insights using modern data platforms such as Azure, Databricks, and MLflow. The specialist will collaborate with various stakeholders to enhance data capabilities and implement scalable AI/ML solutions. Responsibilities:

• Lead development and delivery of ministry-specific analytics and reporting.
• Collaborate with client groups to assess current analytics capabilities and identify improvements.
• Manage end-to-end execution of analytics initiatives including data set delivery and reporting.
• Develop robust statistical models and machine learning algorithms for business scenarios.
• Design data capture, transformation, and processing methods to support model generation.
• Communicate complex quantitative analyses clearly with visuals and summaries.
• Provide interpretation and guidance to stakeholders to transform analytics into actionable insights.
• Run and monitor batch inference jobs on Databricks and troubleshoot model anomalies.
• Support pipeline execution and evaluation runs using internal metrics and custom models.
• Prepare and clean datasets, annotate outputs for error analysis, and maintain reproducible scripts.

Required Skills & Certifications:

• Background in Computer Science, Data Science, or AI/ML (degree or equivalent experience).
• Proficiency in Python and libraries such as pandas, scikit-learn, and PyTorch.
• Experience with Azure data tools including Databricks and MLflow.
• Exposure to large language model (LLM) frameworks like DSPy, LangChain, or Hugging Face.
• Strong analytical, problem-solving, and decision-making skills.
• Experience with statistical analysis, data mining, machine learning, and natural language processing.
• Ability to manipulate and analyze complex, high-volume structured and unstructured data.
• Proficiency in query languages and constructing complex queries.
• Excellent verbal and written communication skills for technical and non-technical audiences.
• Detail-oriented with strong organizational skills for experiment tracking.

Preferred Skills & Certifications:

• Experience with analytical software such as R, PowerPivot, Matlab, SPSS, or SAS.
• Knowledge of data management, financial and business analysis, and database architecture.
• Familiarity with business intelligence tools and information visualization techniques.
• Experience working in government or large enterprise data environments.

Special Considerations:

• Must have experience working onsite for 5 days as required.
• Ability to manage and escalate model anomalies and inference issues promptly.
• Comfortable working within cloud ML environments and adhering to data governance standards.

Scheduling:

• Standard work schedule with possible requirements for monitoring inference jobs and managing experiments.
• Onsite presence required for 5 days during project phases or as specified.