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Company Description Credence Global Solutions, headquartered in Dallas, TX, is a global provider of technology, human resources, and offsite infrastructure solutions for revenue cycle and accounts receivable management. With over 2,500 employees worldwide, the company supports clients in healthcare, telecommunications, utilities, and media & entertainment. Credence Global Solutions focuses on operational excellence, innovative technology, and scalable support models to optimize financial performance and customer engagement. Team members collaborate across geographies to deliver high-impact, data-driven solutions for complex business challenges.
Role Description The Lead Data Scientist is a full-time, on-site role based in the Pune Division. This role is responsible for designing and implementing data science solutions that drive revenue optimization, operational efficiency, and strategic decision-making across multiple industry verticals. Day-to-day responsibilities include leading end-to-end data science projects, building predictive and prescriptive models, performing advanced statistical analysis, and translating business requirements into analytical frameworks. The Lead Data Scientist will guide a team of analysts and data scientists, review and refine methodologies, and present findings and recommendations to senior stakeholders. The role also includes collaborating with engineering and operations teams to operationalize models, improve data quality, and establish best practices in analytics and data governance.
Candidate Requirements
- Bachelor’s or Master’s degree in Computer Science, Data Science, Statistics, Mathematics, or related fields.
- 8–12+ years of experience in data science, AI/ML, GenAI, LLM Ops, and healthcare analytics.
- Proven expertise in Agentic AI, multi-agent orchestration, and autonomous agent development.
- Hands-on experience with cloud platforms (AWS, Azure, GCP) and production deployment of AI models. - Strong knowledge of HIPAA, SOC 2, GDPR, and compliance frameworks in healthcare
Work arrangement
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