This Role:
Data Analytics & Engineering - Data Scientist
Our client :
Fortune 500 Social Media Company
6 Months (Paternity Cover)
Hybrid
Every piece of data helps us understand technologies and growth, identify opportunities, and execute ideas at a global scale. We're able to make smarter, more informed decisions and develop better products.
The main function of the Data Scientist is to produce innovative solutions driven by exploratory data analysis from complex and high-dimensional datasets. The person will be responsible for supporting Enterprise Products at Meta from the data science perspective.
Job Responsibilities:
- Use a flexible, analytical approach to design, develop, and evaluate predictive models and advanced algorithms that lead to optimal value extraction from the data.
- Generate and test hypotheses and analyze and interpret the results of experiments using A/B testing
- Partner with Product and Engineering teams to solve problems and identify trends and opportunities
- Forecast and set product team goals, design and evaluate experiments, monitor key product metrics, understand root causes of changes in metrics, build and analyze dashboards and reports, build key data sets to empower operational and exploratory analysis, and evaluate and define metrics
- Propose what-to-build in the next roadmap, understand ecosystems, user behaviors, and long-term trends, identify new levers to help move key metrics, and build models of user behaviors for analysis or to power production systems
- Influence product teams through the presentation of data-based recommendations, communicate state of business and experiment results to product teams, spread best practices to analytics and product teams, and lead cross-functionally on defining and executing on analyses, including across other data scientists, data engineers, software engineers, user researchers, among other.
- Generate and test hypotheses and analyze and interpret the results of product experiments.
- Produce analysis regarding opportunity sizing, impact sizing, understanding user behavior, develop POVs, and drive decision-making.
Requirements:
- BS degree in a quantitative discipline (e.g., statistics, operations research, econometrics, computer science, engineering).
- Prefer MS in a quantitative discipline with equivalent working experience
- Overall 5+ years of experience
- 4+ years' experience with data and analytics in businesses strategy, marketing, finance, engineering or science
- 3+ years of experience with SQL (Oracle, Vertica, Hive, MySQL, etc.) or a scripting language for data analysis is required.
- 3+ years' experience with supply chain analytics and product analytics
- The ability to communicate effectively in writing, including conveying complex information and promoting in-depth engagement on course topics even with non-technical audience.
- Experience in cross-functional partnership among teams of Engineering, Design, PM, Data Engineering
- Track-record driving product roadmap and execution
- Leading strategic implementation and planning for risk and growth
- Experience with data focused initiatives such as structuring assessments around data quality, and development of reporting aids for both internal and external audiences
- Leveraging data and analytics to identify actionable insights, suggest recommendations through effective communication
- Managing codebase, pipelines, rule logic and underlying data table architectures that support the operational workflows and its various third-party integrations.
Interested parties please click "Apply Now" or send your CV directly to Meenakshi Sharma (EA Reg no: R1545911) at Meenakshi.Sharma@peoplebank.asia.
Peoplebank Singapore Pte Ltd, EA Licence Number: 08C5248.
