Associate Clinical Specialist

1. Position Summary We are seeking an experienced and highly motivated Senior Project Manager to lead a critical, large-scale project focused on implementing an advanced fraud detection system. The successful candidate will be responsible for the entire project lifecycle, managing cross-functional teams, overseeing the integration of Machine Learning (ML) models for fraud analytics, and ensuring timely, compliant, and impactful delivery. This role requires, strong technical acumen in Data Science coupled with exceptional Project and Stakeholder Management skills. 2. Key Responsibilities A. Project and Program Management Lead the planning, execution, monitoring, and closing of the complex fraud detection project, ensuring adherence to scope, budget, and timeline. Develop comprehensive project plans, including detailed work breakdown structures (WBS), resource allocation, and risk management strategies. Manage project documentation, track progress against milestones, and conduct regular project review meetings. Implement and champion Agile / Scrum methodologies tailored for a Data Science / ML development lifecycle. B. Stakeholder and Communication Management Serve as the primary point of contact and liaison between the project team, client, technical specialists (Data Scientists, Engineers), and senior management. Proactively manage and communicate expectations, project status, risks, and issues to all internal and external stakeholders through clear and concise reporting. C. Technical Oversight and Data Science Delivery Provide leadership and guidance to the Data Science team, ensuring the effective development and deployment of Machine Learning algorithms for healthcare insurance claims fraud detection (e.G., anomaly detection, predictive modeling). Must have prior hands-on experience managing data science projects with ML inclusion and understand the nuances of the ML lifecycle (e.G., data ingestion, feature engineering, model training, validation, deployment, and monitoring). Oversee the Data Analytics pipeline, ensuring data quality, integration, and preparation are optimized for ML model consumption. Drive the design, development, and maintenance of interactive Tableau Dashboards to visualize fraud patterns, model performance metrics (Precision, Recall, AUC), and operational insights for both technical and non-technical stakeholders. D. Infrastructure and System Knowledge Possess foundational knowledge of infrastructure and server environments (cloud or on-premise) necessary to host and scale the ML models and data pipelines. 3. Required Qualifications A. Education and Experience Minimum of 5+ years of progressive experience in Project or Program Management. Proven track record of successfully leading at least one full-cycle Data Science project where Machine Learning models were a central component of the solution (e.G., fraud, risk, or recommendation systems). Educational background must include a B.E. / B.Tech. or MBA from a reputed institution. PMP / PRINCE2 certification is a strong plus. B. Technical and Domain Skills Deep understanding of Machine Learning algorithms and their application in fraud detection or similar classification problems. Expert proficiency in Data Analytics and the ability to interpret complex data insights. Demonstrated experience in developing and presenting insights using Tableau Dashboards (or similar advanced BI tools). Working knowledge of data infrastructure, SQL, and concepts of server deployment / maintenance.