Data Scientist, Analytics
Menlo Park, CA | Remote, US
- Perform large-scale data analysis and develop effective statistical models for segmentation, classification, optimization, time series, etc.
- Design and implement reporting dashboards that track key business metrics and provide actionable insights.
- Identify actionable insights, suggest recommendations and influence the direction of the business by effectively communicating results to cross-functional groups.
- Work closely with Product or Engineering & Operations teams to proactively create rule and manage decisions.
- Prioritize leads so that the teams work on the most valuable cases.
- Suggest improvements in the tools and techniques to help scale the team.
- Telecommuting is permitted from anywhere in the U.S.
- Requires a Master’s degree in Computer Science, Mathematics, Statistics, Operations Research, Finance or a related field and 24 months of experience in the job offered or in a related occupation. Requires 24 months of experience involving the following:
- 1. Working with large data sets and network-based data (TCP or HTTP)
- 2. ETL (Extract, Transform, Load) processes
- 3. Relational database (SQL or PL*SQL)
- 4. Quantitative analysis techniques: clustering, regression, pattern recognition, or descriptive and inferential statistics
5. Communicating and presenting results of data analyses.
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. Apply
Job Profile
Telecommuting is permitted from anywhere in the U.S.
Benefits/PerksBenefits Bonus Equity Long term conditions Mental health conditions Pregnancy-related support Religious beliefs
Tasks- Communicating results
- Communicating results to cross-functional groups
- Data Analysis
- Developing reporting dashboards
- Quantitative analysis
- Statistical Modeling
- Working with Product/Engineering teams
Clustering Computer Science Data analysis Design Engineering ETL Finance HTTP Inferential Statistics Optimization Pattern Recognition Quantitative analysis Quantitative Analysis Techniques Recruiting Regression Relational databases Reporting Dashboards Research SQL Statistical modeling Statistics TCP Web
Experience24 months
EducationAnalytics Business Computer Science Data Analysis Design Engineering Finance Master Master’s Degree in Computer Science Master's in Computer Science Mathematics Operations research Physics Related Field Statistics Technology
TimezonesAmerica/Anchorage America/Chicago America/Denver America/Los_Angeles America/New_York Pacific/Honolulu UTC-10 UTC-5 UTC-6 UTC-7 UTC-8 UTC-9