Data Scientist
New
J
JobgetherHealth Technology
BrazilFull-TimeMiddle
Salary not disclosed
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Job Details
- Languages
- Fluent English
- Experience
- 3–5 years
- Required Skills
- PythonSQLMachine LearningProduct AnalyticsPandasData modelingA/B testing
Requirements
- 3–5 years of professional experience as a Data Scientist, preferably in a product-focused environment.
- Strong proficiency in SQL and a solid understanding of data modeling concepts.
- Strong Python skills, ideally including data science and analysis libraries such as Pandas and statistical packages.
- Practical knowledge of A/B testing, statistical analysis, experimentation design, and interpretation of experimental results.
- Familiarity with core product metrics such as DAU, retention, engagement, conversion, and related measures.
- General understanding of machine learning concepts, including model development and evaluation.
- Strong data storytelling and stakeholder communication skills, with the ability to translate technical findings into intuitive business insights.
- Excellent attention to detail, including the ability to validate analyses, identify inconsistencies, and ensure accuracy before sharing results.
- Strong product sense and curiosity about how data can be used to improve digital products and customer experiences.
- Ability to collaborate effectively with Product, Engineering, Data, and business stakeholders.
- Fluent written and spoken English, as the role involves daily collaboration with global teams.
- A growth-oriented mindset, adaptability, initiative, and willingness to learn are highly valued alongside technical expertise.
Responsibilities
- Conduct insightful product analyses to answer business and stakeholder questions and support data-informed decision-making.
- Develop a strong understanding of product functionality and underlying data models to ensure accurate, reliable analysis.
- Partner with Product Managers and Engineers to define meaningful metrics and measurement frameworks for product initiatives.
- Act as a statistical subject-matter expert in experimentation, helping teams design effective and appropriately powered A/B tests.
- Explain statistical concepts such as power, sample size, significance, and experimental limitations in clear, intuitive language.
- Analyze experiment results, determine statistical significance, and identify common experimentation pitfalls, including risks associated with p-hacking.
- Ramp up quickly within a designated product area and become a trusted source of analytical insights.
- Design, launch, and analyze experiments with support and mentorship from experienced Product Data Scientists.
- Contribute feedback on team processes and proactively identify opportunities to improve analytical workflows and experimentation practices.
- Communicate findings through compelling data storytelling, ensuring technical insights are understandable and actionable for stakeholders.
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