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Data Science Specialist II
Localiza&Co. Plan, execute, and analyze A/B tests, multivariate tests, and quasi-experiments, ensuring statistical validity and practical relevance .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in applied statistics, experimentation, and data analysis, with a strong focus on A/B testing, multivariate experiments, and causal inference methods. Proficient in translating complex statistical concepts into actionable business insights while collaborating effectively with cross-functional teams.
Highest-signal resume keywords
Applied StatisticsA/B TestingMachine LearningPythonSQL
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Statistical ModelingCausal InferenceData AnalysisBayesian AnalysisExperimentation
Soft Skills
Clear CommunicationCollaboration
Tools & Technologies
GCPAWSAnalytical Tools
Certifications & Qualifications
Applied Statistics CertificationCausal Inference CertificationDigital Experimentation Certification
Industry Keywords
Data ScienceExploratory AnalysisOptimization OpportunitiesImpact MetricsStatistical Validity
Tech Stack
Tools & technologiesAWSGoogle Cloud PlatformPythonSQL
About the role
Key responsibilities & impact- Plan, execute, and analyze A/B tests, multivariate tests, and quasi-experiments, ensuring statistical validity and practical relevance
- Conduct detailed exploratory analyses to uncover patterns, trends, and optimization opportunities
- Lead statistical modeling and causal inference projects, translating results into business recommendations
- Serve as the technical point of reference for statistics and experimentation within the team
- Propose and implement frameworks for monitoring experiments and impact metrics
- Collaborate with marketing, product, and operations teams to define hypotheses and structure tests
- Ensure clear documentation and accessible communication of results to non-technical stakeholders
- Develop machine learning models focused on generating value for the company and our customers
Requirements
What you’ll need- Solid experience in applied statistics, experimentation, and data analysis
- Strong command of A/B testing, multivariate experiments, and causal inference methods
- Advanced knowledge of statistical models, machine learning, and Bayesian analysis
- Proficiency in Python and SQL
- Ability to translate complex statistical concepts into actionable business insights
- Experience working with large volumes of data and analytical tools
- Intermediate English proficiency
- 5+ years of proven experience in data science, applied statistics, or related fields
- Preferred: experience developing models on GCP and AWS
- Preferred: experience with machine learning models, LLMs, and AI agents
- Preferred: relevant certifications in applied statistics, causal inference, or digital experimentation
- Preferred: active participation in statistics, data science, and applied research communities
Benefits
Comp & perks- Profit sharing
- Food allowance
- Meal allowance
- Medical insurance
- Dental insurance
- Gympass
- Private pension plan
- Transportation allowance
- Allya benefits platform
- Unlimited access to a variety of courses through our Localiza University
- Internal training and development programs
- Discounts on vehicle purchases and rentals