Data Scientist
Onit (company site, opens in a new tab)7+ yrsPuneHybridDirect career pageEst. 20–35 LPA
Posted 2h ago
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Job description
Structured overview of role & requirements
About This Role
- Own end-to-end statistical methodology for customer-facing benchmarking, including comparability modelling and defensibility thresholds.
- Lead data quality improvement programs across multiple source systems, collaborating with Data Engineering on remediation.
- Define and govern approaches for entity resolution, external data supplementation, and privacy-compliant cross-customer analytics while communicating uncertainty to non-technical stakeholders.
Minimum Requirements
- Minimum 7 years experience in applied data science, analytics engineering, or related quantitative roles with ownership of externally facing analytics methodology.
- Strong applied statistics knowledge including sampling, variance, confidence intervals, and small sample judgment.
- Hands-on experience with entity resolution, record linkage, or master data management, plus proficiency in SQL and Python or Ruby; practical experience with Databricks or comparable cloud data platforms.
- Experience diagnosing and remediating large-scale data quality problems and communicating statistical uncertainty clearly to non-technical audiences.
Ideal Candidate Profile
- Experienced in building and validating benchmarks, scoring models, or indices designed for external consumption.
- Comfortable working with anonymisation, aggregation thresholds, and privacy-preserving analytics in regulated or sensitive domains (legal sector experience preferred).
- Skilled at setting data quality SLAs and acceptance criteria in partnership with business stakeholders, with rigorous validation and honest reporting habits.