Expert Fraud Data Scientist Consultant
Quick Summary
Enhance fraud models by collecting, labeling, curating, structuring, and feature engineering data. Design, develop, and improve fraud detection models using machine learning, graph analytics,
Fluent English Education: Master’s degree in a quantitative field such as statistics, computer science, or engineering, ideally with a focus on Fraud Detection. A PhD is a plus.
This is a consultancy mission at a client site, representing Keystone Solutions. As a Keystone Solutions consultant, you will be hired to work on client projects, bringing your expertise and values to every engagement.
- Contribute to the Artificial Intelligence Tribe, delivering efficient and seamless banking experiences through AI applications.
- Work alongside a team of experts including Data Scientists, Machine Learning Engineers, Business Analysts, Scrum Masters, Product Owners, and Managers.
- Develop AI solutions addressing business challenges such as virtual assistants, advanced AI tools, and process automation.
- Act as a Senior Data Scientist specializing in Fraud Detection, with at least 5 years of experience in developing AI applications.
Responsibilities
~1 min read- →Enhance fraud models by collecting, labeling, curating, structuring, and feature engineering data.
- →Design, develop, and improve fraud detection models using machine learning, graph analytics, anomaly detection, and behavioral analytics.
- →Transform large volumes of transactional and customer data into actionable fraud intelligence through feature engineering, data enrichment, and pattern discovery.
- →Collaborate with Fraud Operations, Risk, Compliance, and Product teams to identify fraud trends and translate business needs into scalable analytical solutions.
- →Investigate complex fraud schemes, uncover new attack vectors, and proactively develop detection strategies to mitigate risks.
Requirements
~1 min read- Fluent English
- Master’s degree in a quantitative field such as statistics, computer science, or engineering, ideally with a focus on Fraud Detection. A PhD is a plus. Candidates from other academic backgrounds with strong analytical skills are also welcome.
- At least 7 years of experience in data science, preferably in the financial sector with a focus on fraud detection. Candidates with less experience may be considered if they have strong academic credentials.
- Data Engineering & Management: Hands-on experience manipulating and processing large-scale datasets using SQL, Python (Pandas), Spark/Hadoop, and distributed data processing technologies. Skilled at collecting, enriching, structuring, and validating complex transactional and behavioral data for fraud analytics and machine learning.
- Data Science & Artificial Intelligence: Application of advanced analytical techniques including supervised and unsupervised machine learning, anomaly detection, graph analytics, and network analysis. Experience in building data-centric AI solutions with robust software engineering, high-quality datasets, and state-of-the-art modeling approaches. Experience with generative AI is a plus.
- Programming language: Extensive experience in Python and deploying AI applications in production. Java experience is a plus.
- Team player
- Business oriented
- Quick self-starter, pro-active attitude
- Good communication and influencing skills
- Good analytical and synthesis skills
- Autonomy, commitment, and perseverance
- Ability to work in a dynamic and multi-cultural environment
- Consultancy Nature: You will work on-site as a consultant, representing Keystone Solutions and delivering value to diverse client environments.
- Dynamic Projects: Experience a variety of challenges and projects across multiple client settings, broadening your expertise.
- Turbo-Charged Learning: Benefit from continuous professional development and exposure to cutting-edge technologies and methodologies.
- Skyrocketing Ambition: Keystone Solutions is committed to your career growth, offering opportunities to advance within the consultancy framework.
- Values: As a K-Stone, you bring integrity, excellence, and collaboration to every mission.
Location & Eligibility
Listing Details
- First seen
- August 14, 2026
- Last seen
- August 14, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 51%
- Scored at
- August 14, 2026
Signal breakdown
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