Head of Data Science

**工作地点：新加坡（可混合远程）**

**汇报对象：CEO / 战略产品负责人**

⸻

**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。我们正在构建下一阶段的数据智能中枢。我们希望你具备深厚的数据建模、产品理解与业务驱动能力，来带领我们将海量用户数据沉淀为长期战略优势。

你将主导一支跨领域的数据科学团队，从零到一构建我们的：
- 用户行为模型
- 用户生命周期价值 (LTV ) 预测系统
- 合作伙伴信用评分体系
- 异常行为检测与风控识别系统
- 推荐系统与用户偏好算法

你做的不只是“分析”，而是 **让平台看懂用户，预测趋势，控制风险，并释放B端商业潜力**。

⸻

**职责范围**

**战略与组织：**
- 建立公司级数据科学发展路线图，定义“数据中台”角色与输出能力
- 组建并领导数据科学团队（模型研发、数据产品、工程支持）
- 推动数据能力产品化，服务产品、运营、市场、风控等核心部门

**模型与算法：**
- 设计并部署用户LTV、风险评分、行为标签等核心预测模型
- 参与设计异常行为检测、风险识别、重要客户识别等算法逻辑
- 搭建A/B测试体系，评估模型对业务增长的贡献

**数据驱动产品设计：**
- 与产品经理和研发协作，将模型产出转化为功能或推荐系统
- 为2B端输出代理价值建模、个性化政策定价等策略工具
- 带动“数据驱动运营”文化，改变纯经验驱动决策方式

⸻

**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
- 至少5年以上数据科学或机器学习实战经验，2年以上带队经验
- 精通建模方法（聚类、回归、时间序列、贝叶斯、图模型等）
- 能独立设计用户画像、生命周期、推荐、风控等多类模型
- 熟练使用 Python / R / SQL，了解现代数据栈（如 Airflow、Spark、Kafka）
- 有落地经验：模型必须为业务带来结果（ROI、留存、转化等）

**加分项：**
- 有线上游戏、电商、金融等高用户量平台建模经验
- 对实时风险管理、推荐系统、重要客户评级和异常行为识别有深入理解
- 具备工程思维，懂得如何将模型产品化并部署上线
- 熟悉数据知识产权、数据安全与伦理（数据是企业核心资产）

⸻

**我们能提供的**
- **数据体量**：兆级行为数据、跨产品跨平台完整用户行为轨迹
- **业务场景丰富**：涵盖消费者端体验与企业端合作策略，涵盖推荐系统与风险管理
- **最高决策层支持**：CEO亲自支持构建数据战略，不受中层制约
- **国际化系统**：为全球多个国家客户提供服务，建模难度和潜力均极高
- **高度自由**：你的模型可以变成公司收入与风险控制的主力引擎

⸻

如果你是那个 **不满足于跑报表，而是想让数据变成系核心资产**的人，这个位置就是为你准备的。

⸻

**Location: Singapore (Hybrid Remote Option Available)**

**Reports to: CEO / Head of Strategic Products**

⸻

**Position Overview**

You will lead a cross-disciplinary data science team to build from scratch:

- User behaviour models
- User Lifetime Value (LTV) prediction systems
- Partner credit scoring systems
- Anomaly detection and risk identification systems
- Recommendation engines and user preference algorithms

You will do more than “analyse” — you will enable the system to understand users, predict trends, manage risks, and unlock commercial potential in the B2B domain.

⸻

**Responsibilities**

**Strategy & Leadership**:

- Develop a company-wide data science roadmap, defining the role and deliverables of the “data platform”
- Build and lead a data science team (model development, data products, engineering support)
- Drive productization of data capabilities to serve key departments such as product, operations, marketing, and risk management

**Modelling & Algorithms**:

- Design and deploy core predictive models including user LTV, risk assessment, and behaviour tagging
- Participate in the design of anomaly detection, risk identification, and key account recognition algorithms
- Establish A/B testing frameworks to evaluate model contributions to business growth

**Data-Driven Product Design**:

- Collaborate with product managers and developers to convert model outputs into features or recommendation systems
- Deliver partner value modelling, personalized policy pricing, and strategic tools for the B2B segment
- Foster a “data-driven operations” culture to shift from experience-based to evidence-based decision-making

⸻

**Qualifications**

**Required**:

- Master’s degree or higher in Mathematics, Statistics, Computer Science, Economics, or related fields
- Minimum 5 years of practical experience in data science or machine learning, including 2+ years in team leadership
- Proficient in modelling techniques (clustering, regression, time series, Bayesian, graph models, etc.)
- Able to independently design various models such as user profiling, lifecycle, recommendation, and risk control
- Skilled in Python / R / SQL and familiar with modern data infrastructure (e.g., Airflow, Spark, Kafka)
- Proven track record of deploying models that drive tangible business results (ROI, retention, conversion, etc.)

⸻

**Preferred**:

- Experience with high-user-volume platforms such as digital gaming, e-commerce, or finance
- Deep understanding of real-time risk management, recommendation systems, VIP scoring, and anomaly detection
- Engineering mindset with experience in productizing and deploying models to production
- Knowledgeable in data intellectual property rights, security, and ethics (data as a core enterprise asset)

⸻

**What We Offer**
- **Data scale**:trillions of behavioural data points with cross-product and cross-platform complete user interaction traces
- **Diverse business scenarios**:from consumer experience to enterprise collaboration strategies, covering recommendation and risk management systems
- **Top-level support**:CEO personally champions the data strategy, free from middle management constraints
- **Global system**:serving clients across multiple countries, with high modelling complexity and potential
- **High autonomy**:your models can become key engines driving company revenue and risk control

If you are **not satisfied with merely running reports and want to turn data into the core asset of a platform**, this role is made for you.