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Jobs(31,339)/Senior Data Scientist Role(384)/GRVT TECHNOLOGIES (1) - Senior Data & BI Analyst
GRVT TECHNOLOGIES

GRVT TECHNOLOGIES - Senior Data & BI Analyst

Singapore, Hybrid2mo ago
In OfficeSeniorAPACCryptocurrencyFintechSenior Data ScientistBusiness Intelligence AnalystPythonLookerMetabaseTeam ManagementTeam Leadership

Requirements

• 4-8 years of experience in data analytics, strategy, or business intelligence roles within fintech, crypto, or top-tier tech (e.g., Revolut, Binance, Stripe, Uber). • Highly skilled in SQL, with the ability to independently query and model data. • Proficient in Python/R and BI tools such as Superset, PowerBI, Looker, or Metabase. • Strong grasp of financial modeling, P&L analysis, and business metrics — able to connect data to outcomes. • Experienced in OKR setting, KPI management, and performance tracking across teams. • Excellent communicator who can simplify complex data into executive-level insights. • A hands-on builder who thrives in a fast-moving startup environment. • Bonus: Familiarity with crypto, trading, or on-chain analytics. • 📈 What Success Looks Like • A real-time data control center empowers the CEO and leadership team. • All divisions operate with quantifiable goals and transparent ROI. • Company OKRs and KPIs are rooted in measurable, outcome-driven metrics. • Insights from the Data & Insights team directly shape strategy, capital allocation, and growth initiatives.

Responsibilities

• 1. Company-Wide Performance Intelligence • Build and own the central performance dashboard across all GRVT divisions (Trading, Marketing, BD, Product, Operations). • Create and maintain KPI frameworks that link every department’s goals to company revenue and growth targets. • Generate weekly and monthly CEO reports with clear narratives — what’s working, what’s not, and where to allocate resources. • 2. Strategy & Insight Generation • Analyze company performance and identify growth levers. • Conduct deep dives into metrics like P&L, conversion funnels, and user retention • Develop data-backed forecasts and scenarios (volume, revenue, user growth, liquidity). • Turn findings into strategic recommendations that shape company direction. • 3. KPI Setting & ROI Evaluation • Define and track KPIs for marketing efficiency, BD ROI, and partner venue performance. • Measure impact of every campaign, BD partnership, and feature launch — and recommend optimization levers. • Build ROI models for decision-making on partnerships, vendors, and budgets. • 4. Data Infrastructure & Automation • Set up the data foundation for the company, pipelines, databases, dashboards, and analytics tools (e.g., BigQuery, Looker, Metabase, Mixpanel). • Build and maintain SQL queries and data models directly, minimizing dependency on engineers. • Design self-serve data systems for teams to access accurate and unified data.

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