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Data Scientist, Product Analytics

Lensa

Los Angeles (CA)

On-site

USD 145,000 - 204,000

Full time

3 days ago
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Job summary

Join Meta as a Data Scientist and play a crucial role in shaping impactful products used by billions. Leverage your analytical skills and collaborate with diverse teams to drive data-based decisions that enhance user experiences. This position requires expertise in quantitative analysis and data mining, along with an analytical mindset to navigate complex data challenges. Suitable candidates will have a strong educational background and relevant work experience in analytics.

Qualifications

  • Minimum of 4+ years in analytics and data querying languages.
  • Experience solving analytical problems with a focus on user behaviors and trends.
  • Proficient with tools such as SQL and Python.

Responsibilities

  • Work with large data sets to solve complex problems.
  • Guide teams using data to influence product strategy.
  • Define and test opportunities to improve products.

Skills

Data Analysis
Quantitative Analysis
Data Mining
Scripting (Python)
SQL

Education

Bachelor's degree in Mathematics, Statistics, or a relevant technical field
Master's or Ph.D. Degree in a quantitative field

Job description

1 week ago Be among the first 25 applicants

Lensa is the leading career site for job seekers at every stage of their career. Our client, META, is seeking professionals in Los Angeles, CA. Apply via Lensa today!

Summary

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 wide-range 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 varied 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.

Required Skills

Data Scientist, Product Analytics Responsibilities:

  • 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

Minimum Qualifications

Minimum Qualifications:

  • Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent
  • 4+ years of work experience in analytics, data querying languages such as SQL, scripting languages such as Python, and/or statistical mathematical software such as R (minimum of 2 years with a Ph.D.)
  • 4+ 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

Preferred Qualifications:

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

Public Compensation

$145,000/year to $204,000/year + bonus + equity + benefits

Industry: Internet

Equal Opportunity

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. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.

Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@fb.com.

Seniority level
  • Seniority level
    Mid-Senior level
Employment type
  • Employment type
    Full-time
Job function
  • Job function
    Engineering and Information Technology
  • Industries
    IT Services and IT Consulting

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