远程工作雷达

高级数据分析师 - 欺诈

Senior Data Analyst - Fraud

职能支持限定地区(需当地身份)
公司Moniepoint
薪资未公开
工作地点Remote, Poland
地域资格限定地区(需当地身份)
时区要求无特别要求
用工类型未标注
发布时间2026-08-03
数据来源Greenhouse
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注意地域限制:该职位明确限定在 Remote, Poland 招聘。如果你是位于中国大陆的求职者,通常需要当地工作身份才能投递,或需与雇主确认是否接受独立合同(Contractor)形式合作。

Moniepoint Inc. 是非洲的一站式金融平台,每月帮助 2000 万企业和个人用户便捷地使用支付、银行、信贷、跨境交易和业务管理工具。

作为尼日利亚最大的商户收单机构,我们支持该国大部分的销售点(POS)交易。通过我们的子公司,Moniepoint Inc. 每年处理超过 2500 亿美元的数字支付交易价值。

想了解是什么让 Moniepoint 成为一个令人惊叹的工作场所吗?查看我们关于如何培养创新、团队合作和成长文化的文章。

你将负责以下工作

  • 调查欺诈攻击,量化其影响,并提出清晰的分析结果以推动优先级和响应措施
  • 提出并优化基于规则的缓解方案,与欺诈运营和工程团队合作,确保方案落地实施
  • 构建和维护报告和仪表盘,用于监控欺诈趋势、规则表现和关键运营指标
  • 与欺诈运营、数据科学家、工程师和产品经理紧密合作,确保分析洞察转化为实际行动
  • 主动识别新兴模式,在风险升级前进行预警

要在这个职位上取得成功,你需要具备

  • 作为数据分析师(欺诈方向)或类似职位的实战经验(5 年以上,可通过成就弥补)
  • 强大的问题解决能力
  • 精通 SQL,能够编写复杂的查询,对大规模数据集进行分析和切片
  • 在欺诈、风险或金融服务领域有经验,了解欺诈攻击的运作方式以及如何权衡缓解措施
  • 主动积极的心态——你不会等待被要求;你发现异常情况后会主动深入调查
  • 有 Python 或脚本语言用于数据处理和分析的经验
  • 熟练使用 BI 工具(PowerBI、Looker、Tableau、Superset、Redash 或其他替代工具)
  • 出色的干系人管理能力;你能清晰地向欺诈运营、产品经理、工程师和高层领导传达分析结果,并且知道如何用数据在所有这些角色中影响决策
  • 适应快节奏、跨职能团队的工作环境,能够快速应对优先级的变化
  • 熟练使用电子表格工具(Microsoft Excel 或 Google Sheets,或其他替代工具)
  • 喜欢自主工作和扁平化结构:我们拥有数百万客户,组织结构扁平,因此每个个体都能产生巨大的影响
  • 出色的书面表达能力
查看英文原文

Who We Are

Moniepoint Inc. is Africa’s all-in-one financial platform, helping 20 million businesses and individuals access seamless payments, banking, credit, cross-border, and business management tools each month.

As Nigeria’s largest merchant acquirer, we power most of the country’s point-of-sale (POS) transactions. Through our subsidiaries, Moniepoint Inc. processes over $250 billion in digital payment transaction value annually.

Curious about what makes Moniepoint an incredible place to work? Check out posts on how we cultivate a culture of innovation, teamwork, and growth.

What you will get to do

  • Investigate fraud attacks, quantify their impact, and present clear findings that drive prioritisation and response
  • Propose and refine rule-based mitigations, working with fraud operations and engineering to see them through to implementation
  • Build and maintain reporting and dashboards to monitor fraud trends, rule performance, and key operational metrics
  • Work closely with fraud operations, data scientists, engineers, and product managers to ensure analytical insights translate into action
  • Proactively identify emerging patterns and flag risks before they escalate

To succeed in this role, you should have

  • Proven experience as a Data Analyst (Fraud),  or a similar role (5+ years, can be made up for with accomplishments)
  • Strong problem solving skills
  • Advanced proficiency with SQL. you're comfortable writing complex queries to investigate and slice data across large datasets
  • Experience in fraud, risk, or financial services; you understand how fraud attacks work and how to think about mitigation trade-offs
  • A proactive mindset — you don't wait to be asked; you spot something unusual and you dig in
  • Some exposure to Python or scripting for data manipulation and analysis
  • Proficiency with a BI tool (PowerBI, Looker, Tableau, Superset, Redash, or any other alternative)
  • Strong stakeholder management skills; you can communicate findings clearly to fraud operations, product managers, engineers, and senior leadership — and you know how to influence decisions with data across all of them.
  • Comfort working in fast-paced, cross-functional teams where priorities shift quickly.
  • Proficiency with a spreadsheet tool (Microsoft Excel or Google Sheets, or any other alternative)
  • Enjoy autonomy and a flat structure: we have millions of customers and a flat hierarchy so any individual can have an outsized impact
  • Excellent written and verbal communication skills
  • A drive to learn and master new technologies and techniques
  • A bachelor’s degree in Computer Science, Statistics, Mathematics, Engineering, or any other related field

Experience with the following would be a plus

  • Data governance
  • Python or any other scripting language
  • Git or any other version control tool

What we can offer you

  • Culture - We put our people first and prioritise the well-being of every team member. We have built a company where all opinions carry weight and where all voices are heard. We value and respect each other and always look out for one another. Above all, we are human.
  • Learning - We have a learning and development-focused environment with an emphasis on knowledge sharing, training, and regular internal technical talks.
  • Compensation - You’ll receive an attractive salary, pension, health insurance, annual bonus, plus other benefits.

What to expect in the hiring process

  • A preliminary phone call with the recruiter.
  • Technical take-home task (SQL test).
  • Technical Interview with hiring manager.
  • A behavioural interview with the Head of Data Analytics/Science and Fraud Team.

Moniepoint is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees and candidates.

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