Data Scientist

Data Scientist IILocation: Miami, Florida, United States (On-site)Industry: Hospitals and Health CareWork Setting: On-siteAre you passionate about using data science, machine learning, and AI to transform complex data into meaningful insights that drive better outcomes and business decisions?We are seeking a Data Scientist II to leverage advanced analytics, statistical modeling, and machine learning techniques to solve complex challenges across healthcare, operational, and business domains. This role will work closely with cross-functional teams to develop predictive models, uncover actionable insights, and build scalable data solutions that support data-driven decision-making and innovation.Key ResponsibilitiesApply machine learning, artificial intelligence, and natural language processing techniques to analyze large volumes of structured and unstructured data.Develop predictive and prescriptive models using diverse data sources to identify trends, improve decision-making, and support strategic initiatives.Design and maintain scalable data pipelines that integrate information from multiple systems and sources.Utilize graph-based data modeling and advanced analytics techniques to discover hidden relationships and generate deeper insights.Partner with data engineering, technology, and business teams to deploy analytical solutions into production environments.Develop and validate predictive models for forecasting, risk assessment, optimization, and performance improvement initiatives.Ensure data governance, privacy, security, and compliance standards are followed throughout all analytical activities.Collaborate with stakeholders to understand business requirements and translate them into effective analytical and technical solutions.Document methodologies, model development processes, validation procedures, and analytical findings to ensure reproducibility and transparency.Provide technical guidance, knowledge sharing, and mentorship on data science best practices and analytical methodologies.Required QualificationsBachelor's degree in Data Science, Statistics, Computer Science, Mathematics, Analytics, Bioinformatics, or another quantitative discipline, or equivalent practical experience.3+ years of experience in data science, machine learning, analytics, or related fields.Experience working with large and complex datasets from multiple business systems and data sources.Demonstrated success applying statistical analysis, predictive modeling, and machine learning techniques to solve real-world business problems.Experience transforming data into actionable insights that support operational and strategic objectives.Preferred QualificationsMaster's degree or higher in a quantitative or technical field.Experience with advanced analytics, artificial intelligence, and machine learning model deployment.Exposure to graph databases, vector databases, and knowledge graph technologies.Experience working with cloud-based data platforms and modern data architectures.Familiarity with large language models (LLMs), generative AI technologies, and natural language processing frameworks.Experience supporting advanced analytics initiatives involving complex, multi-source datasets.Technical SkillsStrong proficiency in Python, R, SQL, and data analysis libraries.Expertise in statistical modeling, machine learning algorithms, predictive analytics, and data visualization techniques.Experience working with cloud platforms such as AWS, Azure, or Google Cloud Platform.Knowledge of distributed computing frameworks and large-scale data processing technologies.Familiarity with API integrations, data engineering concepts, and data pipeline development.Experience using modern analytics, reporting, and visualization tools.Desired SkillsStrong analytical thinking and problem-solving capabilities.Ability to translate business objectives into scalable technical solutions.Excellent communication skills with the ability to present complex findings to both technical and non-technical audiences.Strong attention to detail and commitment to data quality, accuracy, and integrity.Ability to manage multiple priorities and projects in a fast-paced environment.Collaborative mindset with experience working across business, technology, and research-focused teams.Self-motivated professional who can work independently while contributing effectively within a team environment.