The Infrastructure Data Science and Engineering group uses statistical and machine learning techniques to support Meta’s infrastructure to enable the continued growth in Meta’s apps and products. We partner with engineering teams supporting Meta’s infrastructure, focusing on strategic initiatives that make our infrastructure more efficient, reliable, and scalable. We are full-stack data scientists, responsible for bringing analytical rigor to solving business and technical problems at Meta-scale. We analyze data, design experiments, build models and communicate our results, fostering a culture of data-driven decision making. We are also team players who believe that diverse strengths and perspectives create synergy and maximize our impact. We form close partnerships with engineering teams and deliver results that have direct impact on Meta’s mission and products.
Ideal candidates are passionate about Meta’s mission and products, possess strong analytical aptitude and coding ability, have excellent collaborative and communication skills, and have hands-on experience working on projects using predictive modeling, pattern mining, optimization, and other quantitative methods.
Research Data Scientist (University Grad) Responsibilities
- Identify appropriate quantitative methods and build relevant data sets to address challenges across different domains in Meta’s infrastructure.
- Develop statistical and machine learning solutions end-to-end through the full life cycle of prototyping, testing, evaluating, deploying and maintaining them at Meta scale.
- Develop measurement solutions and experimentation frameworks to ensure effective data-driven decision making.
- Form close collaborative relationships with other data scientists and engineering partners and contribute to team projects through model development and analyses.
- Communicate project results and recommendations to stakeholders and cross-functional partners.
- Experience applying statistical and machine learning techniques such as hypothesis testing, time series analysis, classification, regression, and clustering to real-world data sets.
- Experience performing data extraction, manipulation, and visualization using programming languages (e.g., Python), scientific computing languages (e.g., R, MATLAB), or SQL.
- Experience with at least one programming language (e.g., Python, Java, C++).
- Experience with scientific computing and analysis packages such as NumPy, SciPy, Pandas, Scikit-learn, dplyr, caret.
- Experience with data visualization libraries such as Matplotlib, Pyplot, seaborn, ggplot2.
- Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment.
- Currently has, or is in the process of obtaining a Bachelor’s degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Degree must be completed prior to joining Meta.
- Experience working on applied research projects using statistical and machine learning techniques on large data sets.
- Experience working with distributed computing tools such as Hadoop, Hive, and Spark.
- Proficiency in data structures and algorithms.
- Experience solving complex problems and comparing alternative solutions, tradeoffs, and diverse points of view to determine a path forward.
- Experience working and communicating cross functionally in a team environment.