Note: The job is a remote job and is open to candidates in USA. Georgia IT, Inc. is seeking a highly analytical and outcome-driven Data Scientist to translate complex business questions into testable hypotheses and deliver evidence-based recommendations. The role involves designing advanced analytical methods, developing predictive models, and collaborating with cross-functional teams to drive measurable business impact.
Responsibilities
- Translate business questions into clear, testable hypotheses with defined success criteria and confidence levels
- Design and execute advanced analytical methods, including segmentation, causal inference, forecasting, propensity modeling, uplift modeling, and experiment design
- Develop and deploy analytical and predictive models into production environments
- Present and defend analytical methodologies, assumptions, results, and recommendations during technical and governance reviews
- Provide timely, evidence-based analysis, including clear communication of inconclusive or negative results
- Maintain regular progress updates covering hypotheses tested, findings, confidence levels, next steps, and potential blockers
- Develop production-quality, version-controlled analytical code, reproducible notebooks, and well-documented analytical workflows
- Partner with Data Engineers to define features, data granularity, historical data requirements, and proactively address data quality or availability gaps
- Translate validated analytical findings into metric definitions and business logic for reporting and visualization
- Collaborate with data science and analytics teams to ensure knowledge transfer, model documentation, and long-term reuse of analytical solutions
- Serve as the analytics lead for assigned projects or pods
- Own analytical quality and ensure the application of sound statistical and data science practices
- Act as a peer reviewer and mentor for internal and client-facing analysts
- Drive analytics best practices, technical excellence, and continuous improvement
- Provide guidance on analytical methodology, model development, experimentation, and interpretation of results
Skills
- 6+ years of professional experience in Applied Data Science or a related field
- Advanced proficiency in Python and/or R and SQL
- Strong experience developing and deploying analytical or machine learning models into production
- Strong foundation in statistics, mathematics, machine learning, experimentation, predictive analytics, and causal inference
- Experience with statistical modeling, hypothesis testing, experimental design, and data-driven decision-making
- Bachelor's or Master's degree in Data Science, Statistics, Mathematics, Computer Science, or a related quantitative discipline
- Strong analytical, problem-solving, communication, and documentation skills
- Experience working with cross-functional teams, including Data Engineers, Data Scientists, and business stakeholders
- Experience in healthcare, medical devices, life sciences, or other regulated industries
- Experience working with experimentation, causal inference, uplift modeling, or propensity modeling
- Experience with production-grade machine learning and analytical workflows
- Familiarity with version control, reproducible research practices, and collaborative data science environments
Benefits
- 100% Remote
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