Data Science has a potential role to play in today's business ecosystems. In the current scenario data is the most valuable asset and data analytics has become a necessity to innovate and grow. Facebook is one of the largest technology conglomerates and social media giants. With more than 2.7 billion active users, the company has been growing its customer base through innovation and technology adoption. Facebook has a core data science team that works on improving user experience by getting deeper insights from a vast variety of data they receive. Facebook currently has many job openings for data scientists in its offices at different locations around the globe. Here, we are listing some of these positions, the roles and responsibilities, and the basic qualifications for applying to these roles.
Location: Dublin, Ireland
Roles and Responsibilities: As a data scientist at Facebook's Data Center organization, the candidate will be expected to collaborate with key stakeholders and lead the development of an analytics program aimed at enhancing the growth of the data center infrastructure. They will be involved in collaborating with the product and engineering teams across different business operations and curating data, to build analytics models, gather data insights, make recommendations, and elaborating requirements for data gathering. The candidate in this position is required to continuously define, compute, track, and validate business and production performance metrics using descriptive, diagnostic, and predictive analytics. Identifying and implementing streamlined processes of data reporting and communication, and deriving effective analytics using tools like R, Python, Tableau, and SQL are important.
Qualifications
Apply for the job here.
Location: London, United Kingdom
Roles and responsibilities: The candidates are expected to work on Facebook's core business products. The primary role includes understanding the user interaction with consumer and business products through quantitative analysis, data mining, and data presentation. The data scientists will be working across product operations, exploratory analysis, product leadership, and data infrastructure. While working in data infrastructure, the candidate will leverage Hadoop and Hive primarily. Supporting and executing the company's product decisions and launches, identifying trends and opportunities by collaborating with product and engineering teams, are other responsibilities of the data scientists.
Qualifications:
Apply for the job here.
Location: Tel Aviv, Israel
Roles and Responsibilities: As a data scientist for the product team, the candidate is expected to work as a key member, solve problems, and identify opportunities and trends. The candidate should be able to apply their expertise in quantitative analysis and data presentation to think beyond the numbers and understand user interaction with the company's growth products. Other responsibilities include executing product launches and decisions, monitoring key product metrics, setting KPIs and goals, designing and evaluating experiments. The job role demands conducting exploratory analysis and identifying levers to aid the movement of key metrics.
Qualifications:
Apply for the job here.
Location: Singapore
Roles and requirements: The candidate is expected to work with the eDiscovery and Information Governance legal team. The data scientist will have to work cross-functionally to design and implement datasets for regulatory compliance. They have to collect data from different products and leverage it in legal matters. The candidates are desired to automate analyses and author pipelines through SQL and Python-based ETL framework. They need to develop dashboards to make data pipelines comprehensible for non-technical stakeholders. Stay updated on new structured data sources and work in collaboration with different teams and business operations across the organization.
Qualifications:
Apply for the job here.
Location: Zurich, Switzerland
Roles and responsibilities: The candidate is expected to deliver world-class products by building and leading an efficient data science team. They should work in collaboration with the engineering and product teams to identify trends and opportunities. The candidate should effectively understand the user interaction with different products and their growth by applying their knowledge in quantitative analysis, data mining, and presentation of data. Data science managers are expected to develop and maintain reports, dashboards, and monitoring metrics for analyzing the product performance. Managing the development of data resources along with gathering requirements, organizing sources, and supporting and launching products are other desired job roles.
Qualifications:
Apply for the job here.
Location: Menlo Park, san Fransisco, California
Roles and Requirements: The position is for data scientists in Business Messaging Monetization and the company is looking for candidates who can drive the strategy to enable the growth of Click-to-WhatsApp ads and deliver value to millions of businesses that leverage these products. The candidate is expected to design and evaluate experiments and product holdouts. Understanding user behavior, ecosystems, and long-term trends are critical for this job role. Data scientists in this position should be able to set team goals, evaluate and define metrics, monitor key product metrics, measuring the progress of key metrics against goals, and proposed developments in the next roadmap. They are expected to partner with other product and engineering teams, and influence and execute product launches.
Qualifications:
Apply for the job here.
Join our WhatsApp Channel to get the latest news, exclusives and videos on WhatsApp
_____________
Disclaimer: Analytics Insight does not provide financial advice or guidance. Also note that the cryptocurrencies mentioned/listed on the website could potentially be scams, i.e. designed to induce you to invest financial resources that may be lost forever and not be recoverable once investments are made. You are responsible for conducting your own research (DYOR) before making any investments. Read more here.