Data Scientist

About this role

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Skills you'll use

What you'll do

• Collect, clean, and analyze large structured and unstructured datasets from multiple internal and external sources
• Conduct thorough exploratory data analysis (EDA) to understand data distributions, relationships, outliers, and missing value patterns
• Profile and audit datasets to assess data quality, completeness, consistency, and fitness for modeling
• Investigate and document data lineage — understanding where data originates, how it flows, and how it transforms across systems
• Identify and resolve data anomalies, inconsistencies, and integrity issues in collaboration with data engineering teams
• Develop a deep understanding of the business domain and the underlying data that represents it — including what each field means, how it is captured, and what its limitations are
• Translate raw, messy, real-world data into clean, well-understood analytical datasets ready for modeling and reporting
• Apply statistical techniques such as correlation analysis, hypothesis testing, variance analysis, and distribution fitting to extract meaningful signals from noise

Who can apply

• Build and deploy machine learning models including regression, classification, clustering, NLP, and time-series analysis
• Design, evaluate, and analyze A/B experiments and controlled tests using causal inference techniques
• Develop data-driven recommendations backed by rigorous statistical reasoning
• Write clean, production-ready code in Python or R
• Collaborate with data engineers to build reliable data pipelines and feature stores
• Deploy and monitor ML models using MLOps best practices on cloud infrastructure
• Build dashboards and self-serve analytics tools to support stakeholder decision-making
• Strong ability to interrogate unfamiliar datasets and quickly develop a working understanding of their structure, semantics, and quirks

About Gradera

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