Data Scientist, Product Analytics - Machine Learning
Sunnyvale, CA | Bellevue, WA | Menlo Park, CA | New York, NY
Meta
Giving people the power to build community and bring the world closer together
As 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.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product’s ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches including Machine Learning to test them. You will research challenging ML questions to inform experimentation and can build ML prototypes. .
Communication and influence: You won’t simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.Data Scientist, Product Analytics - Machine Learning Responsibilities
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
Product leadership: You will use data to shape product development, quantify new opportunities, identify upcoming challenges, and ensure the products we build bring value to people, businesses, and Meta. You will help your partner teams prioritize what to build, set goals, and understand their product’s ecosystem.
Analytics: You will guide teams using data and insights. You will focus on developing hypotheses and employ a diverse toolkit of rigorous analytical approaches, different methodologies, frameworks, and technical approaches including Machine Learning to test them. You will research challenging ML questions to inform experimentation and can build ML prototypes. .
Communication and influence: You won’t simply present data, but tell data-driven stories. You will convince and influence your partners using clear insights and recommendations. You will build credibility through structure and clarity, and be a trusted strategic partner.Data Scientist, Product Analytics - Machine Learning 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.
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
- Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.
- 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.
- Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent practical experience.
- 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).
- Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
- Masters or Ph.D. Degree in a quantitative field.
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.
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Tags: Big Data Computer Science Data Mining Engineering Finance Hadoop Machine Learning Mathematics ML infrastructure ML models Physics Prototyping Python R Research Spark SQL Statistics VR
Perks/benefits: Career development Equity / stock options Health care Salary bonus
Region:
North America
Country:
United States
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