数据分析师 / Data Analyst

岗位概述

我们是一家由经验丰富的IT专家创立的中小型软件公司,专注于为客户提供CRM及其他定制化软件应用和解决方案。我们致力于不断壮大和培养人才团队,以应对多变且充满挑战的市场需求,持续推动创新产品的开发。公司处理大规模的用户及系统交互数据,正积极提升核心数据能力。你将与数据科学负责人紧密合作,从底层数据中挖掘高价值特征,支持用户行为建模、生命周期预测、风险识别及策略优化等关键任务。

这不是一份做报表的岗位,而是一份深入业务、构建策略、参与模型验证的分析核心角色。

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岗位职责

• 清洗与整理用户行为数据、交易记录、交易日志、关键业务操作记录等核心数据表
• 编写高效 SQL,支持建模特征提取、数据集构建与迭代优化
• 与数据科学家协作,参与用户生命周期建模、风险识别模型等开发工作
• 分析模型输出结果,生成可解释报告与洞察,支持业务与产品团队决策
• 建立基础用户分群、渠道行为评估等分析框架
• 协助搭建数据字典与分析基础表,提升公司整体数据理解与应用效率
• 必要时支持 BI 可视化报表配置(如用户行为监控、A/B测试等)

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任职资格

必备条件:

• 具备数学、统计、计算机、经济学等领域硕士或以上学历

• 扎实的 SQL 能力,能处理大型日志表和复杂行为拼接逻辑

• 熟悉数据仓库结构,理解 ETL 流程和数据表设计逻辑

• 有行为数据分析经验,懂如何从原始记录中提取有价值的行为特征

• 理解基本的统计学、数据建模流程,能协助变量工程和实验分析

• 主动性强,具备业务理解力,能提出问题而不仅响应需求

加分项:

• 有游戏、电商、金融平台等用户行为数据分析经验

• 熟悉Python 或 R,有变量衍生、模型评估、A/B实验经验

• 熟悉分布式数据环境(如Hive、Spark)

• 能阅读复杂模型输出,与科学家讨论分析逻辑

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我们提供的环境

• 大规模真实用户数据(非样本),涵盖行为、资金、内容偏好等

• 与顶尖数据科学家、策略制定者直接协作的机会

• 灵活办公环境,可远程,可部分时区差

• 高度影响力的角色,数据成果直接改变产品、策略和收益

Position Overview

We are an SME software house founded by experienced IT professionals, specializing in delivering CRM and other customised software applications and solutions for our clients. We are committed to growing and nurturing our talent pool to meet the ever-changing and challenging market demands, continuously driving the development of innovative products. Our company works with large-scale user and system interaction data and is actively enhancing its core data capabilities. You will work closely with the Head of Data Science to extract high-value features from foundational data, supporting key tasks such as user behaviour modelling, lifecycle prediction, risk identification, and strategy optimization.

In this role, you will work closely with the Head of Data Science to extract high-value features from foundational data, supporting key initiatives such as user behaviour modelling, lifecycle prediction, risk identification, and strategy optimization.

This is not a traditional reporting role. It's a strategic, analysis-driven position where you will dive deep into business logic, contribute to modelling efforts, and play a vital role in data-driven decision making.

Key Responsibilities

• Clean and structure key data tables, including user behaviour logs, transaction records, and business activity logs
• Write efficient SQL to support feature engineering, dataset construction, and iterative experimentation
• Collaborate with data scientists on lifecycle models, risk identification models, and more
• Analyse model outputs and deliver interpretable reports and insights to guide business and product decisions
• Build foundational frameworks such as user segmentation and channel behaviour evaluation
• Assist in building data dictionaries and foundational analytical tables to improve data understanding and usability across the company
• Provide support for BI dashboards when needed (e.g., user behaviour monitoring, A/B testing reports)

Requirements

Must-Have:

• Hold a master's degree or above in Mathematics, Statistics, Computer Science, Economics, or related fields.
• Strong SQL skills, capable of working with large log tables and complex event stitching logic
• Familiarity with data warehouse structures, ETL processes, and table design principles
• Experience analysing behavioural data, and skilled at extracting meaningful features from raw logs
• Solid understanding of basic statistics and data modelling workflows, including feature engineering and experiment analysis
• Proactive and business-oriented mindset, able to ask the right questions and not just respond to requests

Nice-to-Have:

• Experience analysing user behaviour data from gaming, e-commerce, or financial platforms
• Proficient in Python or R, with hands-on experience in feature engineering, model evaluation, and A/B testing
• Familiarity with distributed data environments (e.g., Hive, Spark)
• Ability to interpret complex model outputs and engage in analytical discussions with data scientists

What We Offer

• Access to large-scale real-world user data, including behaviour, transaction, and preference signals
• Direct collaboration with top-tier data scientists and strategy stakeholders
• Flexible work arrangements, including remote work and time zone offsets
• High-impact role where your work directly influences products, strategy, and business outcomes