- Utilize advanced knowledge of data mining, business intelligence, Hadoop/Hive, SQL, Excel, and Tableau to drive efficient analytics and reporting.
- Identify actionable insights, suggest
recommendations and influence the direction of product designs by effectively communicating results to cross functional groups, including WhatsApp leadership. - Leverage data and
mathematical principles to provide insights about user behavior, inform business decisions, and solve large scale data infrastructure problems based on data mining on large, complex data
sets. - Predict and understand user patterns through metric analysis.
- Work cross functionally to define problem statements, collect anonymized data, build analytical models and make
recommendations. - Partner with Product and Engineering teams to solve problems and identify trends and opportunities.
- Build and analyze dashboards, reports and key data sets to
empower operations and exploratory analysis. - Automate analyses and author data pipelines via SQL and Python based ETL framework.
- Apply expertise in Hadoop and Hive for data
infrastructure. - Develop strong business partnerships with WhatsApp leadership by translating strategic questions into structured analyses, defining success metrics, and developing
reporting channels. - Assist in designing hypothesis testing experiments, analyze data collected, and present results.
- Conduct ad hoc data analysis based on current team needs.
- Complete
root cause analysis of different workflows in order to quantify problems, operationalize goals and identify priorities. - Train team members on the use of reporting tools and lead data-driven
business case solving courses. - Telecommute from anywhere in the US permitted.
- Employer will accept a Master’s degree in Business Analytics, Marketing Analytics, Computer Science, Applied Sciences, Mathematics, Physics, or related field and 2 years of work experience in job offered or in a business/product analytics-related occupation. Experience must include two years of experience in the following:
- 1. Relational database (SQL or PL*SQL)
- 2. Large scale data processing infrastructures using distributed systems (Hadoop, Hive, MapReduce, or MPI)
- 3. Scripting language (Python, R, PHP, or Perl)
- 4. Statistics (hypothesis testing and regressions)
- 5. Using languages and packages such as R, Pandas, MATLAB, SPSS, SAS, or Stata
- 6. Communicating and presenting results of data analyses
- 7. Operating strategic projects with cross-functional partners
- 8. Initiating and driving projects to completion with minimal guidance.
Individual pay is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base salary, Meta offers benefits. Learn more about benefits at Meta.