We are a data science-driven special investigations unit that uses data across employers, insurers, and contractors to prevent fraud in the insurance space, with a focus on workers' compensation and personal injury fraud. We're building smarter, more predictive systems that will shape the future of fraud detection in blue-collar industries.
We need a talented Data Scientist to work at the intersection of data and engineering, applying statistical analysis, machine learning, and thoughtful experimentation to uncover fraud and assess labor risk. You should have a strong problem-solving mindset and excellent communication skills.
Due to the high volume of applications we anticipate, we regret that we are unable to provide individual feedback to all candidates. If you do not hear back from us within 4 weeks of your application, please assume that you have not been successful on this occasion. We genuinely appreciate your interest and wish you the best in your job search.
Commitment to Equality and Accessibility:
At MLabs, we are committed to offer equal opportunities to all candidates. We ensure no discrimination, accessible job adverts, and providing information in accessible formats. Our goal is to foster a diverse, inclusive workplace with equal opportunities for all. If you need any reasonable adjustments during any part of the hiring process or you would like to see the job-advert in an accessible format please let us know at the earliest opportunity by emailing [email protected].
MLabs Ltd collects and processes the personal information you provide such as your contact details, work history, resume, and other relevant data for recruitment purposes only. This information is managed securely in accordance with MLabs Ltd’s Privacy Policy and Information Security Policy, and in compliance with applicable data protection laws. Your data may be shared only with clients and trusted partners where necessary for recruitment purposes. You may request the deletion of your data or withdraw your consent at any time by contacting [email protected].
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