Airtm - Data Scientist
Requirements
• Strong SQL and Python skills for data analysis and modeling. • Experience with dbt for analytics engineering workflows. • Experience building dashboards in Tableau (or similar BI tools). • Solid foundation in statistics, experimentation, and hypothesis testing. • Ability to work cross-functionally and communicate insights effectively. • Experience building or prototyping machine learning models. • Exposure to cloud platforms (AWS) for data storage or analytics workloads. • Experience working with data pipelines or collaborating closely with data engineering teams. • Knowledge of feature engineering and model evaluation concepts. • Experience with version control (Git). • We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
Responsibilities
• Collaborate with product and business teams to define analytical questions, success metrics, and KPIs. • Build and maintain analytics foundation using SQL and dbt, enabling reliable reporting and self-serve analytics. • Design, build, and maintain Tableau dashboards that bring metrics to life and support day-to-day decision-making. • Perform A/B testing and experimentation, including experiment design, statistical inference, significance testing, and result interpretation. • Perform ad-hoc, exploratory, and statistical analyses to uncover insights and validate hypotheses. • Communicate findings clearly to both technical and non-technical stakeholders, translating data into actionable recommendations. • Partner with stakeholders to iterate on metrics, dashboards, and analyses as business needs evolve.
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