Visiting Researcher, Research Data Scientist (PhD)

Menlo Park, California

Posted in Retail

This job has expired.

Job Info

The Infrastructure Data Science and Quantitative Engineering group uses statistical and machine learning techniques to support the operations and enable the continued growth of Meta's infrastructure. We partner with teams supporting all of Meta's infrastructure, focusing on long-term strategic initiatives that make Meta 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 an environment of data-driven decision making. We are seeking a Visiting Researcher to join our team. Individuals in this role are expected to be PhD researchers who have hands-on experience with a deep background in statistical and machine learning techniques, and can collaborate effectively with partner engineering organizations, fellow data scientists and leadership. The length of the term would be a minimum of 6 months. As a Research Data Scientist, you will need to develop subject matter expertise, build trust with partners, recognize the biggest opportunities, create and drive strategy, and leverage data science methodologies to solve hard problems. In your work, you may provide guidance and coordinate with other data scientists to help achieve the goals in broad areas of operation. 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 with predictive modeling, pattern mining, optimization, and other quantitative methods.

Visiting Researcher, Research Data Scientist (PhD) Responsibilities:

  • Identify appropriate quantitative methods and build relevant data sets to address challenges across different domains in Meta's infrastructure.
  • Build pragmatic and scalable end-to-end solutions to large-scale web, mobile, and data infrastructures utilizing rigorous statistical and machine learning solutions.
  • Develop measurement solutions and experimentation frameworks to ensure effective data-driven decision making.
  • Drive projects forward by forming close collaborative relationships with other data scientists and engineering partners to reach the end deliverable, such as production-grade models and algorithms or analyses that shape the technical vision of partner teams.
  • Employ languages and tools like Python, R, SQL, and others to drive efficient data exploration and modeling.
  • Communicate project results and recommendations to stakeholders and cross-functional partners.
  • Lead and provide technical mentorship to data scientists, to ensure continuous up-leveling of our expertise.

Minimum Qualifications:

  • Currently has, or is in the process of obtaining, a PhD degree in a quantitative field such as Computer Science, Statistics, Engineering, Operations Research, and other related technical fields
  • Experience doing quantitative analysis including experience with SQL, other programming languages (e.g., Python) or statistical/mathematical software (e.g., R, SAS, MATLAB)
  • Experience with statistics methods such as forecasting, time series, hypothesis testing, classification, clustering or regression analysis
  • Experience developing production software systems such as data pipelines, deployed machine learning models, or dashboards
  • Experience presenting findings from statistical and machine learning methods to different audiences through effective communication skills
  • 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
  • Experience initiating and driving projects to completion with minimal guidance

Preferred Qualifications:

  • 2+ years of experience doing complex quantitative analysis and working with distributed (i.e., Hive, Hadoop or similar databases) or highly complex datasets
  • 2+ years experience communicating complex research in a clear, precise, and actionable manner

Facebook is proud to be an Equal 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.Facebook 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

This job has expired.

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