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Senior Data Scientist (Contract) — Customer Identity & Entity Resolution
About The Company
NES Group Ltd is part of a global engineering and technical staffing organization with more than 90 years of combined experience. Operating across sectors including Oil & Gas, Power & Renewables, Chemicals, Construction & Infrastructure, Life Sciences, Mining, and Manufacturing, the organization connects clients with skilled professionals around the world. With a network of more than 80 offices in 45 countries, NES Group Ltd supports businesses with the expertise they need across locations and project environments. Its contractor support extends beyond recruitment, with assistance that may include visa and work permit processes, accommodation, and benefits packages, helping professionals work safely and compliantly on client assignments.
About The Role
NES Group Ltd is seeking a Senior Data Scientist for a contract opportunity focused on customer identity and entity resolution. In this role, you will help strengthen how customer records are matched, linked, and represented across data systems. You will combine data science, machine learning, and graph-based approaches to address identity challenges that cannot be resolved reliably through rules alone.
You will work with customer data, architecture, and platform stakeholders to improve the customer-spine architecture, reduce identity drift, and establish measurable standards for matching quality. Your work will also support integration with a trusted golden layer and contribute to a reusable identity-resolution framework. This opportunity suits a hands-on data scientist who can translate complex identity challenges into reliable, scalable solutions and communicate the implications of those solutions to technical partners.
Qualifications
Candidates should bring demonstrated experience in entity resolution, record linkage, and fuzzy matching, including the ability to assess and improve matching accuracy across imperfect or inconsistent datasets. You should have practical experience applying machine-learning methods to identity resolution and understand how to operationalize models through MLOps practices. Familiarity with feature stores and production machine-learning workflows is important.
Experience with Customer Master data or Master Data Management (MDM) is required. The successful candidate will be comfortable working across data pipelines and customer data structures, investigating identity issues, and collaborating with stakeholders responsible for data platforms and governance. Experience with governed identity hierarchies, matching-quality metrics, and golden-layer integration is an advantage. Clear communication, sound analytical judgment, and the ability to deliver reusable technical solutions are also important.
Responsibilities
Design, develop, and improve machine-learning and graph-based approaches to customer identity resolution where deterministic rules are insufficient. Analyze record-linkage challenges and apply appropriate fuzzy-matching and modeling techniques to connect records while accounting for ambiguity, data quality, and changing customer information.
Contribute to the evolution of the customer-spine architecture and help identify and reduce identity drift across systems. Define, document, and monitor matching-quality metrics so stakeholders can evaluate performance and understand trade-offs. Support the integration of resolved identity data with the golden layer, working with relevant teams to align technical outputs with data requirements.
Build a reusable identity-resolution framework that can support consistent implementation across use cases. Apply appropriate MLOps practices to make solutions maintainable and operational, and work with feature-store capabilities where relevant. Share findings, document methods, and collaborate with data and platform stakeholders to support adoption and continuous improvement.
Benefits
This contract opportunity offers the chance to contribute to a significant customer-data initiative within a global staffing and engineering network. NES Group Ltd provides contractor support beyond recruitment, which may include assistance with visas and work permits, accommodation, and access to market-leading benefits packages, subject to the assignment, location, and applicable terms. The team can also support contractors with relevant onboarding and compliance requirements for their client engagement.
Equal Opportunity
NES Group Ltd is committed to fair and respectful recruitment. Applicants will be considered based on relevant skills, experience, and role requirements. We welcome candidates from diverse backgrounds and encourage all qualified professionals to apply.
About The Company
NES Group Ltd is part of a global engineering and technical staffing organization with more than 90 years of combined experience. Operating across sectors including Oil & Gas, Power & Renewables, Chemicals, Construction & Infrastructure, Life Sciences, Mining, and Manufacturing, the organization connects clients with skilled professionals around the world. With a network of more than 80 offices in 45 countries, NES Group Ltd supports businesses with the expertise they need across locations and project environments. Its contractor support extends beyond recruitment, with assistance that may include visa and work permit processes, accommodation, and benefits packages, helping professionals work safely and compliantly on client assignments.
About The Role
NES Group Ltd is seeking a Senior Data Scientist for a contract opportunity focused on customer identity and entity resolution. In this role, you will help strengthen how customer records are matched, linked, and represented across data systems. You will combine data science, machine learning, and graph-based approaches to address identity challenges that cannot be resolved reliably through rules alone.
You will work with customer data, architecture, and platform stakeholders to improve the customer-spine architecture, reduce identity drift, and establish measurable standards for matching quality. Your work will also support integration with a trusted golden layer and contribute to a reusable identity-resolution framework. This opportunity suits a hands-on data scientist who can translate complex identity challenges into reliable, scalable solutions and communicate the implications of those solutions to technical partners.
Qualifications
Candidates should bring demonstrated experience in entity resolution, record linkage, and fuzzy matching, including the ability to assess and improve matching accuracy across imperfect or inconsistent datasets. You should have practical experience applying machine-learning methods to identity resolution and understand how to operationalize models through MLOps practices. Familiarity with feature stores and production machine-learning workflows is important.
Experience with Customer Master data or Master Data Management (MDM) is required. The successful candidate will be comfortable working across data pipelines and customer data structures, investigating identity issues, and collaborating with stakeholders responsible for data platforms and governance. Experience with governed identity hierarchies, matching-quality metrics, and golden-layer integration is an advantage. Clear communication, sound analytical judgment, and the ability to deliver reusable technical solutions are also important.
Responsibilities
Design, develop, and improve machine-learning and graph-based approaches to customer identity resolution where deterministic rules are insufficient. Analyze record-linkage challenges and apply appropriate fuzzy-matching and modeling techniques to connect records while accounting for ambiguity, data quality, and changing customer information.
Contribute to the evolution of the customer-spine architecture and help identify and reduce identity drift across systems. Define, document, and monitor matching-quality metrics so stakeholders can evaluate performance and understand trade-offs. Support the integration of resolved identity data with the golden layer, working with relevant teams to align technical outputs with data requirements.
Build a reusable identity-resolution framework that can support consistent implementation across use cases. Apply appropriate MLOps practices to make solutions maintainable and operational, and work with feature-store capabilities where relevant. Share findings, document methods, and collaborate with data and platform stakeholders to support adoption and continuous improvement.
Benefits
This contract opportunity offers the chance to contribute to a significant customer-data initiative within a global staffing and engineering network. NES Group Ltd provides contractor support beyond recruitment, which may include assistance with visas and work permits, accommodation, and access to market-leading benefits packages, subject to the assignment, location, and applicable terms. The team can also support contractors with relevant onboarding and compliance requirements for their client engagement.
Equal Opportunity
NES Group Ltd is committed to fair and respectful recruitment. Applicants will be considered based on relevant skills, experience, and role requirements. We welcome candidates from diverse backgrounds and encourage all qualified professionals to apply.
