Data Scientist
Core
Design, develop, and implement cohesive data integration and advanced analytics solutions involving structured and unstructured data for mission-critical initiatives in regulated and public-sector environments.
Role type
Senior IC data scientist (analytics & modeling)
Builds
Predictive models, forecasting solutions, optimization models, text mining, and network analytics
Domain
Public sector, government ecosystems, regulated industries
Deliverable
production ML models | product features
Required skills
predictive modeling, forecasting, operations research, text mining, network analytics, feature selection, hyper-parameter optimization, model validation, visualization, AWS SageMaker, Amazon QuickSight, Python (Pandas, NumPy, SciPy, Scikit-Learn, XGBoost, PySpark), SQL, production software engineering routines, test-driven development, CI/CD, object-oriented programming
Preferred skills
data engineering, data ingestion, transformation, pipeline development, Agentic AI, Generative AI, LLM-based solutions, Retrieval-Augmented Generation, knowledge assistants, document intelligence, conversational analytics
Technologies
AWS SageMaker, Amazon QuickSight, Python, Pandas, NumPy, SciPy, Scikit-Learn, XGBoost, PySpark, Git
Responsibilities
Develop and manage the end-to-end lifecycle of analytics projects from requirement gathering to production; Lead or support data requirement and analytics use-case workshops with business and technical stakeholders; Propose, implement, and validate data science models ensuring explainability, fairness, scalability, and security; Participate actively in software development processes and documentation; Produce high-quality client-ready deliverables and technical documentation; Perform end-to-end testing and validation of migrated applications; Proactively research client business context and industry trends; Contribute to the development of reusable project assets
Seniority
Mid-to-Senior, hands-on IC