Lead Data Analyst

Job Responsibilities

* Prioritize the business aspect over technical skills; analyze data to provide actionable insights for decision-making. * Identify and quantify gaps in user retention, collaborate with cross-functional teams to develop strategies for improvement. * Serve as the single source of truth for business insights, collaborating with product, growth, and GTM teams. * Analyze and monitor key metrics such as activation rates, retention rates, WAU, CPA, and conversion indicators. * Offer strategic business recommendations based on data analysis to drive retention and user engagement.

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IMPORTANT — REQUIRED VIDEO SUBMISSION   Every applicant MUST submit a 2–3 minute Loom video explaining a software project they have personally worked on.   In your video, please explain the project's purpose, your specific role, the technologies involved, and how you approached the technical challenges.   Speak naturally, as if you were explaining the project to a potential US client. We want to evaluate your English fluency, technical knowledge, confidence, speaking voice, and ability to communicate without a script.   Proposals without a Loom video link will NOT be considered. No exceptions.

As a Senior AI Analytics Engineer in our Data Team, you will serve as a key link between Data Engineering, Technology, and Product teams. Your primary responsibilities will involve operationalizing AI/LLM models, developing scalable data transformation pipelines, standardizing data models, and implementing best practices.

In addition to your core duties in analytics engineering, you will also be involved as a technical Business Analyst on certain data projects, collaborating with business units to translate operational needs into clear technical requirements.

* Monitor and analyze core metrics, conduct diagnostics to provide insightful business recommendations. * Establish measurement frameworks for product launches to track success metrics. * Collaborate with cross-functional teams to evaluate market opportunities and run experiments to inform investment decisions. * Develop regular reporting rhythms and self-serve dashboards for team members. * Translate data analysis into actionable insights for product, growth, and executive teams. * Implement AI tools in the data analysis stack to improve efficiency.

Lead live video interviews and technical discussions with prospective US clients.   Explain software solutions, technical approaches, architecture, and development processes clearly.   Confidently answer spontaneous technical questions.   Discuss project requirements, implementation strategies, timelines, and potential challenges.   Communicate our development team's capabilities effectively.   Ask insightful questions to identify client needs and demonstrate technical understanding.   Coordinate with our developers before interviews to understand project-specific details.   Help turn technical discussions into successful project engagements.

Data & AI Architecture: Develop and manage production-quality data models to connect raw data streams with downstream tools and BI, utilizing AI tools for data documentation, writing SQL/Python transformations, handling warehouse dialect conversions, and troubleshooting pipeline errors.

Analytics Engineering: Establish standardized data modeling approaches and build strong semantic layers to deliver clean, reliable data for analytics and reporting downstream.

Business & Requirements Analysis: Lead scoping discussions with various stakeholders to convert business requirements into functional specifications, user stories, and data mapping documents.

Business Logic Translation: Manage the alignment of data definitions across departments, a critical task that requires human intervention.

Data Quality & Governance: Implement automated testing, monitoring, and governance frameworks to ensure high reliability.

Performance Optimization: Enhance query performance, reduce warehouse costs, and streamline pipeline orchestration.

Cross-functional and External Stakeholder Delivery

Manage operational requirements, timelines, and issue resolution among different internal teams such as Corporate Development, Product, Operations, Finance, Engineering, Legal, and Compliance.

Oversee end-to-end operational workflows for new digital asset integrations and product offerings, from assessment to launch and ongoing maintenance.

* Business-minded data analyst with experience in driving retention and growth in consumer products. * Proficiency in SQL, data analytics tools, and at least one scripting language like Python. * Strong analytical skills with the ability to deliver impactful insights that drive business decisions. * Demonstrated success in leveraging AI tools for analysis and decision-making. * Excellent communication skills to effectively convey complex analysis to non-technical stakeholders.

* Familiarity with gaming metrics and AB testing frameworks. * Experience with subscription and payment data analysis. * Background in intelligent AI, consumer AI, or creator economy products.

IT & Networking

Python

SQL

Cpa

More skills

Native or near-native American English fluency.   Strong verbal communication and conversational confidence.   A mature, authoritative speaking style. A naturally deep, resonant voice is strongly preferred.   Hands-on software development experience or a solid technical background.   Familiarity with modern software technologies such as .NET, Python, JavaScript, React, Node.js, APIs, databases, and cloud infrastructure.   Ability to discuss unfamiliar technical requirements intelligently.   Experience communicating with US clients in technical or consulting environments.   Comfortable leading Zoom or Google Meet meetings independently.   Availability during US business hours.   You do not need to be an expert in every technology. However, you must have enough practical software engineering knowledge to discuss projects intelligently, handle follow-up questions, and communicate technical concepts convincingly.   Engagement Details   Remote, part-time position.   Flexible schedule based on client interview bookings.   Compensation based on experience and qualifications.   Opportunity for long-term collaboration as our agency grows.     - typescript / node.js - go - rust - python - postgres - clickhouse - redis - kafka or similar messaging systems - docker - linux environments - evm rpc internals - websocket infrastructure   ecosystem familiarity   - ethereum, arbitrum, base, optimism, bsc - hyperliquid / hyperevm - foundry - ethers.js / viem - geth / erigon / nethermind - dex and amm mechanics - liquidity math, slippage, gas strategy, routing logic   this role is not suitable for   - frontend-only developers - nft or basic dapp experience only - tutorial-level web3 developers - candidates without production systems experience   we value engineers who have built real systems where correctness, latency, and reliability matter under load. we care less about buzzwords and more about concrete systems you have personally built and operated.     - system architecture decisions - bottlenecks and tradeoffs - failure modes and recovery strategies - latency considerations in real systems - production debugging experience   working style   - remote - async-first - low bureaucracy - high ownership - engineering-driven team - direct technical communication   we strongly prefer practical engineering depth over polished presentation. if you have built or worked on systems involving realtime data, trading infrastructure, blockchain execution, or latency-sensitive backend systems, please include details of those systems when applying.

Role

Data Analyst