Data Scientist

Georgia IT Inc.
San Jose, CA, United States
17 days ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
10 years minimum
Working hours
Regular working hours
Job source

Tech stack

Business Logic Python (Programming Language) Machine Learning SQL Databases

Job description

· Translate approved business questions into testable hypotheses sized at one to three days with clear exit criteria and confidence levels.

· Design and execute analytical methods including segmentation, causal inference, forecasting, propensity modeling, uplift modeling, and experiment design.

· Defend analytical methodology and findings during review and governance forums.

· Provide an initial evidence-based answer within five business days, including inconclusive or negative results.

· Maintain daily progress updates covering hypotheses tested, findings, confidence level, next steps, and blockers.

· Develop production-quality, version-controlled analytical code with reproducible notebooks and documented assumptions.

· Partner with Data Engineers to define features, granularity, historical data requirements, and address data gaps proactively.

· Convert validated findings into metric definitions and business logic for visualization and reporting.

· Collaborate with client data scientists and provide comprehensive model documentation for handover and reuse.

Additional Responsibilities (Senior Data Scientist)

· Serve as analytics lead for the pod.

· Own analytical quality across engagements.

· Act as peer reviewer and mentor internal and client analysts.

· Drive analytics best practices and technical excellence.

Requirements

We are seeking highly analytical and outcome-driven Data Scientists to translate business questions into testable hypotheses, apply advanced analytical methods, and deliver evidence-based recommendations that drive measurable business impact., · Senior Data Scientist: 10+ years of applied data science experience.

· Advanced proficiency in Python and/or R and SQL.

· Demonstrated experience deploying analytical models into production.

· Strong foundation in statistics, machine learning, experimentation, and predictive analytics.

· Strong background in statistics, mathematics and with data science degree

· Healthcare, medical device, life sciences, or regulated-industry experience preferred.

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