Research Data Scientist

Design and conduct data-driven research studies and experiments.

Collect, clean, transform, and analyze large and complex datasets.

Develop statistical, predictive, and machine-learning models to solve research problems.

Identify patterns, trends, correlations, and relationships within datasets.

Define appropriate research questions, hypotheses, metrics, and evaluation methods.

Apply statistical methods and experimental techniques to validate research findings.

Develop data pipelines and analytical workflows when required.

Use Python, R, SQL, or other appropriate tools for data analysis and modeling.

Evaluate model performance and improve algorithms based on research objectives.

Visualize and communicate complex findings through charts, dashboards, and reports.

Review academic literature and stay current with developments in data science, statistics, and machine learning.

Collaborate with researchers, engineers, product teams, and domain experts.

Prepare technical reports, research papers, presentations, and documentation.

Ensure data quality, reproducibility, and appropriate documentation of research processes.

Support the development and testing of new analytical methods and research prototypes.

Present research findings and recommendations to technical and non-technical stakeholders.

Follow appropriate data privacy, security, and ethical research practices.

Mentor junior data scientists or research team members when required.

Perform other duties assigned by the Research Lead or Data Science Manager.