Data Masked
Data Scientist, Product Analytics - Machine Learning
Data Masked, Menlo Park, California, United States, 94029
Data Scientist, Product Analytics - Machine Learning
Join to apply for the
Data Scientist, Product Analytics - Machine Learning
role at
Meta .This range is provided by Meta. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.Base pay range
$173,000.00/yr - $242,000.00/yrAs a Machine Learning Data Scientist at Meta, you will have the opportunity to do groundbreaking applied machine learning work that will shape the industry and the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs). By applying your Machine Learning knowledge and technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance, and others. You will use data and analysis to identify and solve product development’s biggest challenges in ML systems through insights as well as prototyping ML solutions. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond. In contrast to most ML engineering roles, ML in product analytics allows you to work out ML solutions for broader less defined problems where you can use not just ML knowledge but also strong analytical skills to break down complex problems into well-learnable parts.Responsibilities:
Partner with cross-functional engineering and product teams to derive quantitative understanding of Meta’s ML infrastructure and ML applications to inform future strategy and design ML solutions for complex problems.Define, understand, and test opportunities and levers to improve the product through ML models and applications, and drive ML-modeling roadmaps through your insights and recommendations.Build ML prototyping solutions.Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.Minimum Qualifications:
A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.) with a focus on one of the following: ML Modeling, Ranking, Recommendations, or Personalization systems.Experience with applying machine learning techniques to big data systems (e.g., Spark and Hadoop) with TB to PB scale datasets.Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).Preferred Qualifications:
Masters or Ph.D. Degree in a quantitative field.About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
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Join to apply for the
Data Scientist, Product Analytics - Machine Learning
role at
Meta .This range is provided by Meta. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.Base pay range
$173,000.00/yr - $242,000.00/yrAs a Machine Learning Data Scientist at Meta, you will have the opportunity to do groundbreaking applied machine learning work that will shape the industry and the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Reality Labs). By applying your Machine Learning knowledge and technical skills, analytical mindset, and product intuition to one of the richest data sets in the world, you will help define the experiences we build for billions of people and hundreds of millions of businesses around the world. You will collaborate on a wide array of product and business problems with a diverse set of cross-functional partners across Product, Engineering, Research, Data Engineering, Marketing, Sales, Finance, and others. You will use data and analysis to identify and solve product development’s biggest challenges in ML systems through insights as well as prototyping ML solutions. You will influence product strategy and investment decisions with data, be focused on impact, and collaborate with other teams. By joining Meta, you will become part of a world-class analytics community dedicated to skill development and career growth in analytics and beyond. In contrast to most ML engineering roles, ML in product analytics allows you to work out ML solutions for broader less defined problems where you can use not just ML knowledge but also strong analytical skills to break down complex problems into well-learnable parts.Responsibilities:
Partner with cross-functional engineering and product teams to derive quantitative understanding of Meta’s ML infrastructure and ML applications to inform future strategy and design ML solutions for complex problems.Define, understand, and test opportunities and levers to improve the product through ML models and applications, and drive ML-modeling roadmaps through your insights and recommendations.Build ML prototyping solutions.Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses.Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.Minimum Qualifications:
A minimum of 6 years of work experience in analytics (minimum of 4 years with a Ph.D.) with a focus on one of the following: ML Modeling, Ranking, Recommendations, or Personalization systems.Experience with applying machine learning techniques to big data systems (e.g., Spark and Hadoop) with TB to PB scale datasets.Experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).Preferred Qualifications:
Masters or Ph.D. Degree in a quantitative field.About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram, and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology.Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.
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