Location: Remote, working India Standard Time hours.
We are seeking a skilled Product Scientist to join our team, focusing on one of our enterprise clients within the FinSys Team.
Role Overview:
As a Product Scientist, you will be instrumental in analyzing and optimizing the onboarding and signup processes for employers, particularly those sponsoring jobs or purchasing paid subscriptions. Your responsibilities will include identifying friction points, generating actionable insights, and improving user conversion on billing and payment pages. Additionally, you will enhance the initial user journey and overall engagement across Indeed’s billing and payment touchpoints.
Key Responsibilities:
Analyze the onboarding and signup flow for employers to identify and address friction points.
Optimize user conversion on billing and payment pages by generating actionable insights.
Improve the initial user journey and engagement across Indeed’s billing and payment touchpoints.
Conduct and analyze 8+ A/B experiments throughout the year, ensuring the collection of accurate and reliable data.
Ensure that all experiments conclude with data we are confident in, addressing current data reliability issues.
Requirements
Required Skills and Qualifications:
Bachelor’s degree in Statistics, Mathematics, Data Science, Engineering, or a related quantitative field, or equivalent practical experience.
Experience with analysis applications (e.g., extracting insights, performing statistical analysis, or solving business problems) and coding (e.g., Python, R, SQL).
Strong SQL skills and exceptional attention to granular details in data visualization.
Strong product sense, with the ability to analyze funnels, identify key business trends, and understand the impact of drivers on funnel conversion and feature usage.
Experience in identifying opportunities for business or product improvement and defining and measuring the success of these initiatives.
Proven experience working closely with Engineers and Product Managers to provide product-centric insights.
Experience in developing new models, methods, analyses, and approaches, particularly in time series forecasting, statistical and causal inference, and classification methods.
Expected Outcomes:
By the end of this term, you will be expected to have successfully concluded all experiments with accurate, reliable data, significantly improving our confidence in the results.
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