Job
Description
As a Data Analyst at Driffle, you will play a crucial role in analysing vast data sets to derive insights that drive decision-making across various departments including Business, Marketing, and Operations. Key Responsibilities: - Collaborate with the tech and product team to define key performance indicators (KPIs) for the product. - Design and implement robust metric tracking systems, ensuring consistent and accurate data collection. - Design A/B tests and other experiments to validate product hypotheses. Analyse results to provide insights on product changes and their impact on user behaviour. - Generate product insights from data analyses to suggest new features or improvements. - Bridge the gap between data and product by translating findings into actionable product strategies. - Dive deep into the data to determine the root causes of observed patterns or anomalies. - Identify key drivers influencing metrics and advise on potential interventions. - Conduct ad-hoc analyses to answer specific business questions or to inform product strategy. - Create clear and impactful visualizations that convey complex data insights. - Collaborate with stakeholders to communicate findings, provide recommendations, and influence product direction. Required Skills: - Strong proficiency in Python or R. - Demonstrated experience in SQL (experience with other data storage technologies is a plus). - Mastery of statistical hypothesis testing, experiment design, and causal inference techniques. - Hands-on experience with A/B and multivariate testing methodologies. - Familiarity with behavioural data and experimentation platforms such as Mixpanel, Growth Book. - Strong visual, written, and verbal communication skills and ability to convey complex analytical results to non-technical audiences. Preferred Requirements: - Familiarity with ML algorithms and techniques, including but not limited to regression models, clustering, and classification. - Expertise in building, evaluating, and deploying ML models. - Experience in e-commerce, marketplace business-models, proficiency in digital marketing. As a Data Analyst at Driffle, you will play a crucial role in analysing vast data sets to derive insights that drive decision-making across various departments including Business, Marketing, and Operations. Key Responsibilities: - Collaborate with the tech and product team to define key performance indicators (KPIs) for the product. - Design and implement robust metric tracking systems, ensuring consistent and accurate data collection. - Design A/B tests and other experiments to validate product hypotheses. Analyse results to provide insights on product changes and their impact on user behaviour. - Generate product insights from data analyses to suggest new features or improvements. - Bridge the gap between data and product by translating findings into actionable product strategies. - Dive deep into the data to determine the root causes of observed patterns or anomalies. - Identify key drivers influencing metrics and advise on potential interventions. - Conduct ad-hoc analyses to answer specific business questions or to inform product strategy. - Create clear and impactful visualizations that convey complex data insights. - Collaborate with stakeholders to communicate findings, provide recommendations, and influence product direction. Required Skills: - Strong proficiency in Python or R. - Demonstrated experience in SQL (experience with other data storage technologies is a plus). - Mastery of statistical hypothesis testing, experiment design, and causal inference techniques. - Hands-on experience with A/B and multivariate testing methodologies. - Familiarity with behavioural data and experimentation platforms such as Mixpanel, Growth Book. - Strong visual, written, and verbal communication skills and ability to convey complex analytical results to non-technical audiences. Preferred Requirements: - Familiarity with ML algorithms and techniques, including but not limited to regression models, clustering, and classification. - Expertise in building, evaluating, and deploying ML models. - Experience in e-commerce, marketplace business-models, proficiency in digital marketing.
