Hire senior data analysts who turn questions into decisions
Senior data analysts who own metrics, experiments and dashboards, work in your product and business teams, and answer questions on the same day they are asked.
By the Ryz Labs team · Updated October 2026
Hiring data analysts through Ryz gets you senior analysts who can take a vague business question, find the right data and come back with an answer people act on. They are top 1% of the candidates we interview, they work on your team and in your tools, and they work on US business hours.
What our data analysts work on
Our analysts sit close to the people making decisions: product managers, finance, operations, growth and leadership. They work in SQL first, with Python or R when the question needs it, on top of Snowflake, BigQuery, Redshift or Postgres, and they present in Looker, Tableau, Power BI, Mode or Hex. Typical work:
- Defining core metrics such as activation, retention, net revenue retention and unit economics, then documenting them so every team counts the same way.
- Product analytics in Amplitude, Mixpanel or warehouse event tables: funnels, cohorts, feature adoption and drop-off analysis.
- Designing, sizing and reading A/B tests, including guardrail metrics and honest write-ups when a test is inconclusive.
- Self-serve dashboards for operating reviews, with clear definitions and fewer one-off requests.
- Forecasts and scenario models for pipeline, demand, staffing or churn.
- Ad hoc deep dives that answer one specific question, such as why conversion dropped in a region last month.
Skills we vet for
- Analytical SQL. CTEs, window functions, date spines, deduplication and joins that do not quietly multiply rows.
- Metric design. Choosing a numerator and denominator that match the question, and spotting when a metric can be gamed.
- Experimentation. Power and sample size, randomization units, novelty effects, multiple comparisons and when to use CUPED or other variance reduction.
- Statistics in practice. Confidence intervals, regression basics, survivorship and selection bias, and Simpson's paradox in real segment data.
- Python or R for analysis. pandas or the tidyverse, notebooks that someone else can rerun, and basic plotting with matplotlib, seaborn or ggplot2.
- BI tooling. LookML, Tableau calculated fields and level-of-detail expressions, Power BI measures, and when a semantic layer like dbt metrics is worth it.
- Data modeling awareness. Reading dbt models, understanding grain and knowing when to ask a data engineer for a new table instead of patching it in a dashboard.
- Communication. A one-page summary with a recommendation, caveats and the decision it supports, written in clear English.
How we vet data analysts
Our recruiters source analysts who have supported real decisions, not just built charts. Our in-house ARC system ranks the pipeline, and candidates complete structured NTRVSTA AI interviews that cover SQL, statistics and how they explain a result to a non-technical stakeholder. Recruiters review every candidate before and after the interview, then send a curated shortlist. AI scores are advisory, and humans make the decisions.
Sample interview topics
- Weekly active users rose 12% after a release, but revenue did not move. What would you check first, and what are the likely explanations?
- Write a query for 30-day retention by signup cohort when users can have multiple accounts and events arrive late.
- An experiment shows a significant lift on day three, and the PM wants to ship. What do you check before agreeing?
- Two dashboards report different revenue for the same month. Walk through how you would reconcile them.
- Sales asks for a churn prediction model by Friday. How do you scope a version that is useful and honest about its limits?
Ways to hire data analysts
| Option | Best for | Trade-offs |
|---|
| Freelance marketplace | A single dashboard or a one-time analysis | Freelancers rarely build the business context that makes analysis useful over time. |
| Staffing or recruiting agency | Filling a role with a defined BI tool list | Tool keywords say little about judgment, statistics or communication. |
| In-house recruiting | A permanent analytics function | Slow to staff, and hiring managers spend weeks screening take-home tests. |
| Ryz Labs staff augmentation | Adding senior analysts to product, growth or finance teams | You set priorities and metric definitions. Works best with a warehouse already in place. |
| Ryz Labs AI pod team | Pairing analytics with an AI system, such as forecasting or document analysis | A dedicated pod with data, ML and backend engineers. Scoped as a team with a plan up front. |
If you only need a few hours of dashboard work through a self-serve marketplace, or you want a strategy consultancy to run a transformation program, Ryz is not the right fit.
Why hire data analysts from Latin America
Analysis is a conversation. The best analysts ask follow-up questions while the stakeholder still remembers why they asked, join the weekly business review live and adjust the cut of the data in the meeting. Working on US business hours makes that possible without late calls or overnight handoffs.
Senior analysts in the region have worked in marketplaces, payments, consumer apps and logistics businesses with large, messy datasets. They write in clear English, present to executives and are used to working directly with product and finance leads rather than through a ticket queue.
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FAQ
What is the difference between a data analyst and a data scientist?
Analysts focus on describing what happened and why, defining metrics and supporting decisions. Data scientists spend more time on predictive models and statistical methods. Many senior analysts do light modeling, and we will tell you which profile fits your questions.
Which BI tools do your analysts use?
Looker, Tableau, Power BI, Mode, Hex and Metabase are common, along with Amplitude and Mixpanel for product data. We match analysts to the stack you already run.
What does it cost to hire a data analyst through Ryz?
$7,000 to $15,000 per engineer per month, scoped per team. You get a plan, a price and the names of the people who would do the work before you sign anything.
How do Ryz analysts work with our team, and what hours do they keep?
Ryz analysts work on your team, reporting to your leads. They work on US business hours, so they join your standups and business reviews. Talk to us to scope your team.
Can one analyst support several teams?
Yes, if priorities are clear. Many clients start with one senior analyst shared across product and growth, then add a second once the request queue shows where demand is.
Questions we didn't answer? Email info@ryzlabs.com.