Job description

Our client is seeking a highly skilled and experienced Senior Data Scientist to join their pioneering team, focusing on advanced predictive analytics. This is a fully remote role, enabling you to work from anywhere within the US. You will be instrumental in leveraging complex datasets to build sophisticated models that drive critical business decisions in the insurance sector. The ideal candidate will possess a strong foundation in statistical modeling, machine learning, and data visualization, coupled with a deep understanding of insurance operations. Key Responsibilities: Design, develop, and deploy advanced machine learning models for predictive analytics, including risk assessment, fraud detection, customer segmentation, and claims forecasting. Explore and analyze large, complex datasets from various sources to identify trends, patterns, and insights relevant to the insurance industry. Develop and maintain robust data pipelines for model training and deployment. Collaborate with stakeholders across underwriting, claims, marketing, and product development to understand business needs and translate them into data science problems. Communicate complex analytical findings and recommendations to both technical and non-technical audiences through clear visualizations and presentations. Stay at the forefront of data science research and best practices, evaluating and implementing new algorithms and techniques. Build and mentor junior data scientists, fostering a culture of learning and innovation. Ensure the ethical and responsible use of data and models, adhering to privacy regulations. Optimize model performance, accuracy, and scalability. Develop A/B testing frameworks to evaluate the impact of implemented models. Contribute to the overall data strategy and roadmap of the organization. Qualifications: Ph.D. or Master's degree in Data Science, Statistics, Computer Science, Mathematics, or a related quantitative field. Minimum of 7 years of hands-on experience in data science, with a strong emphasis on predictive modeling and machine learning. Proficiency in programming languages such as Python or R, and experience with relevant libraries (e.g., scikit-learn, TensorFlow, PyTorch, pandas, NumPy). Expertise in statistical modeling techniques, including regression analysis, time series analysis, and experimental design. Strong experience with SQL for data extraction and manipulation. Proven ability to work with big data technologies (e.g., Spark, Hadoop) and cloud platforms (e.g., AWS, Azure, GCP). Excellent data visualization skills using tools like Tableau, Power BI, or Matplotlib. Demonstrated experience in the insurance industry or a strong understanding of insurance data and processes. Exceptional problem-solving and analytical abilities. Outstanding communication and presentation skills. This fully remote position allows for a flexible work environment while contributing significantly to our client's data-driven success.

Requirements