Meta
Data Scientist, Product Analytics

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Data Scientist Role at Meta
Meta is seeking a Data Scientist to drive product strategy and decision-making across our family of applications, including Facebook, Instagram, Messenger, WhatsApp, and Meta's emerging platforms. In this role, you will apply advanced quantitative analysis, statistical modeling, and data-driven storytelling to shape how billions of people experience our products. You will partner closely with Product, Engineering, Research, and cross-functional teams to identify opportunities, define success metrics, design experiments, and translate complex data into clear, actionable recommendations that influence product direction and investment decisions at scale.
Responsibilities
- Work with large and complex data sets to solve a wide array of challenging problems using different analytical and statistical approaches
- Apply technical expertise with quantitative analysis, experimentation, data mining, and the presentation of data to develop strategies for our products that serve billions of people and hundreds of millions of businesses
- Identify and measure success of product efforts through goal setting, forecasting, and monitoring of key product metrics to understand trends
- Define, understand, and test opportunities and levers to improve the product, and drive roadmaps through your insights and recommendations
- Partner with Product, Engineering, and cross-functional teams to inform, influence, support, and execute product strategy and investment decisions
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Minimum Qualifications
- Bachelor's degree in Mathematics, Statistics, a relevant technical field, or equivalent
- 4+ years of experience with data querying languages (e.g. SQL), scripting languages (e.g. Python), and/or statistical/mathematical software (e.g. R)
- 4+ years of experience solving analytical problems using quantitative approaches, understanding ecosystems, user behaviors & long-term product trends, and leading data-driven projects from definition to execution [including defining metrics, experiment design, and communicating actionable insights]


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Preferred Qualifications
- Master's or Ph.D. Degree in a quantitative field
- Demonstrated ability to integrate AI tools to optimize/redesign workflows and drive measurable impact (e.g., efficiency gains, quality improvements)
- Demonstrated ongoing AI skill development (e.g., prompt/context engineering, agent orchestration) and staying current with emerging AI technologies
- Experience adhering to and implementing responsible, ethical AI practices (e.g., risk assessment, bias mitigation, quality and accuracy reviews)
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