Data Scientist

Role: Data Scientist
Location: Remote

Job Description

We are seeking an experiencedData Scientist II to join Meta's growing analytics team. The ideal candidate will use advanced statistical, analytical, and machine learning techniques to uncover insights and drive data-informed business decisions. This position requires strong technical expertise, analytical thinking, and the ability to collaborate across teams to deliver impactful data-driven solutions.

Key Responsibilities

• Apply expertise instatistics, machine learning, programming, data modeling, and simulation to recognize patterns, identify opportunities, and develop innovative analytical solutions.

• Design, build, and evaluatepredictive models and advanced algorithms to extract maximum value from data.

• Generate and test hypotheses, interpret the results of product experiments, and translate findings into actionable recommendations.

• Collaborate with product and engineering teams to translate prototypes into scalable products and features.

• ProvideBusiness Intelligence (BI) anddata visualization support, including dashboards for online customer service and ad-hoc analytical requests.

• Work extensively with large datasets to support Meta's $50B advertiser analytics initiatives.

Required Skills & Qualifications

• Proficiency inPython and/orR for data analysis and model development.

• Experience withbig data tools (e.g., Hadoop, Spark) anddata visualization platforms (e.g., Tableau, Power BI).

• Strong understanding ofSQL and ability to manipulate large, complex datasets.

• Excellent written and verbal communication skills with the ability to convey complex insights clearly.

• Minimum3 years of hands-on experience in data science, applied research, or analytics.

• Bachelor's or Master's degree in Computer Science, Statistics, Mathematics, Economics, Engineering, or a related field.

Preferred Qualifications

• Experience indigital advertising, social media analytics, orconsumer data platforms.

• Background working in large-scale data environments.

• Familiarity withA/B testing,data validation, andperformance measurement frameworks.