Data Scientist, Product Analytics

Meta; Seattle (WA); On-site; USD 114,000 - 171,000; Full time

Job summary

Join a forward-thinking company as a Data Scientist, where your analytical skills will shape the future of products used by billions. In this exciting role, you will leverage one of the richest data sets globally to influence product strategy and drive impactful decisions. Collaborate with diverse teams across Product, Engineering, and Marketing to tackle challenging problems and deliver actionable insights. This innovative firm is dedicated to skill development and career growth, providing a dynamic environment where your contributions will make a significant difference. Embrace the opportunity to work on high-impact projects that redefine user experiences and drive business success.

Benefits

Bonus

Equity

Comprehensive benefits

Qualifications

• 2+ years of experience in analytics and data querying languages.
• Proficient in quantitative approaches and data-driven project execution.

Responsibilities

• Work with large data sets to solve complex problems using analytical approaches.
• Partner with cross-functional teams to inform product strategy and decisions.

Skills

Data Analysis

Statistical Analysis

Data Mining

Quantitative Analysis

Scripting (Python)

SQL

Data Visualization

Education

Bachelor's degree in Mathematics, Statistics, or a relevant field

Master's or Ph.D. Degree in a quantitative field

Tools

R

Job description

As a Data Scientist at Meta, you will shape the future of people-facing and business-facing products we build across our entire family of applications (Facebook, Instagram, Messenger, WhatsApp, Oculus). By applying your 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. 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.

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 to test them.

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 Responsibilities

1. Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches.
2. 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.
3. Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends.
4. Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations.
5. Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions.

Minimum Qualifications

1. Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent.
2. 2+ years of work experience in analytics and data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R).
3. 2+ years of experience solving analytical problems using quantitative approaches, understanding ecosystems, user behaviors & long-term product trends, and leading data-driven projects from definition to execution [including defining metrics, experiment, design, communicating actionable insights].

Preferred Qualifications

1. Master's or Ph.D. Degree in a quantitative field.

$114,000/year to $171,000/year + bonus + equity + benefits

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.

Equal Employment Opportunity and Affirmative Action

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, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics.

Meta is committed to providing reasonable support (called accommodations) in our recruiting processes for candidates with disabilities, long term conditions, mental health conditions or sincerely held religious beliefs, or who are neurodivergent or require pregnancy-related support. If you need support, please reach out to [e-mail].

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