Job description

The Product Data Analytics Team analyzes a combination of product usage and product performance data to derive meaningful insights that would serve as a guide to better product and decision making for our business leaders. As a member of the data science team, you will work with diverse and highly collaborative teams of product managers, engineers, and other data analysts to drive product impact. You will be working on exciting and challenging projects, and convert the insights into real changes, for both new initiatives and scaled products. You are a self-starter who is excited about data, excels in product logic thinking, clear communication, and brings distinctive problem-solving skills and impeccable quantitative modeling experience. As a Data Scientist, you will be working on designing and monitoring core metrics, identifying the root causes for metric movements through deep dive into the models. The role will cover a wide range of model-driven solutions to deliver superior business outcomes through research and analyses. In particular, this role will leverage the causal structure of user behavior, identify trends and opportunities for user growth and great ecosystem, and guide the product team to make the best decisions. Responsibilities - Leverage data to solve challenging business problems from full-spectrum of product and business lines, using analytical and statistical approaches. - Build and improve applicable statistical models, e.g. LTV and ROI prediction, to guide user growth-related decisions. - Initiate model-driven analysis to provide deep insights into various products. Catch the common rule of problems and establish the inter-product analytic paradigm. - Work with Product, Operations, Engineering and cross-functional teams to drive product development through analytic, statistical, and algorithmic expertise. - Design, run and analyze A/B experiments to inform and execute the product strategy, and ultimately improve the product and support business decisions. Minimum Qualification(s) - Master’s degree in a quantitative discipline (e.g. Statistics, Operations Research, Computational Biology, Computer Science, Mathematics, Economics). - 5+ years of experience in statistical modeling (Regression, Classification, Clustering, etc.) and machine learning (deep learning), and experience in user-level modeling - 2+ years of experience with leading a team - Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences - Proficiency in SQL, Python/R Preferred Qualification(s) - Solid communication and collaboration skills with the ability to work effectively with internal teams in a diversified environment - Passion for the Internet industry and data analysis. - Self-starter with the ability to acquire an in-depth understanding of the relation between data and user experience/product growth.

Requirements

Must-haves

Leverage data to solve challenging business problems from full-spectrum of product and business lines, using analytical and statistical approaches.
Build and improve applicable statistical models, e.g. LTV and ROI prediction, to guide user growth-related decisions.
Initiate model-driven analysis to provide deep insights into various products. Catch the common rule of problems and establish the inter-product analytic paradigm.
Work with Product, Operations, Engineering and cross-functional teams to drive product development through analytic, statistical, and algorithmic expertise.
Design, run and analyze A/B experiments to inform and execute the product strategy, and ultimately improve the product and support business decisions.
Minimum Qualification(s)
Master’s degree in a quantitative discipline (e.g. Statistics, Operations Research, Computational Biology, Computer Science, Mathematics, Economics).
5+ years of experience in statistical modeling (Regression, Classification, Clustering, etc.) and machine learning (deep learning), and experience in user-level modeling
2+ years of experience with leading a team
Ability to conduct rigorous analysis and communicate conclusions to both technical and non-technical audiences
Proficiency in SQL, Python/R
Solid communication and collaboration skills with the ability to work effectively with internal teams in a diversified environment
Passion for the Internet industry and data analysis.
Self-starter with the ability to acquire an in-depth understanding of the relation between data and user experience/product growth.

Nice-to-haves

Preferred Qualification(s)

Application prep

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Keywords to mirror

machine learningsqlpython

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