Data Scientist Talent Network
New
J
JobgetherData Science
Based in IndiaContractJunior
Salary not disclosed
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Job Details
- Experience
- 1+ years
- Required Skills
- PythonSQLMachine LearningA/B testing
Requirements
- 1+ years of professional experience in data science or a closely related analytical field.
- Experience working in a leading technology, research, quantitative, AI, or similarly rigorous environment is highly valued.
- Strong proficiency in Python and SQL.
- Strong knowledge of statistical modeling, machine learning, experimentation, and causal inference.
- Demonstrated ability to conduct rigorous exploratory data analysis.
- Experience developing or evaluating machine learning pipelines, feature engineering, experiments, or technical reports.
- Exceptional written communication skills.
- Strong analytical judgment and a highly detail-oriented approach.
- Ability to identify methodological issues, inconsistencies, and technical inaccuracies.
- Ability to apply evaluation standards consistently while exercising sound professional judgment.
- Comfortable receiving feedback and calibrating judgment.
- Strong independent working skills.
Responsibilities
- Participate in future data science projects involving the evaluation, assessment, or improvement of AI-generated and human-created technical work.
- Design precise, task-specific grading criteria for data science deliverables, including exploratory data analyses, statistical models, machine learning pipelines, experimentation and A/B testing work, feature engineering, notebooks, and technical reports.
- Evaluate data science outputs against established criteria, ensuring assessments are technically rigorous, consistent, and evidence-based.
- Review analytical approaches, statistical reasoning, modeling decisions, experimental designs, and conclusions for accuracy and quality.
- Provide detailed written explanations supporting evaluation scores, clearly identifying strengths, weaknesses, errors, and areas for improvement.
- Apply consistent and defensible judgment when assessing complex or ambiguous technical work.
- Ensure evaluations are reproducible by grounding assessments in objective evidence and clearly defined standards.
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