Inspira Financial

Compensation

Full Description

Inspira is seeking highly skilled and intellectually curious Data Scientist to join our dynamic Data Science & Analytics Organization. The role is central to driving data informed decision-making across the organization by developing predictive models, uncovering insights and building scalable analytic solutions.   The ideal candidate will possess a strong foundation in statistical modeling, machine learning, and data engineering, along with the ability to communicate complex findings in a clear and actionable manner to both technical and non-technical stakeholders.   Duties & Responsibilities: * Develop and deploy predictive models and machine learning algorithms to solve business problems and optimize performance * Conduct exploratory analysis to identify trends, patterns and opportunities * Collaborate with cross-functional teams to define business questions and translate them into analytical frameworks * Build and maintain data pipelines and ensure data quality, integrity, and accessibility * Design and deliver visualizations and dashboards that communicate insights effectively * Apply statistical techniques to test hypotheses validate model performance * Document methodologies, code and findings to ensure transparency and reproducibility Qualifications * Bachelors degree in Data Science, Statistics, Mathematics or related field (Masters degree preferred) * 3 – 5+ years of experience in data science or advanced analytics role * Proficiency in programming languages such as Python, SQL and R * Proficiency with statistical modeling and machine learning * Familiarity with cloud data platforms (Snowflake, Azure) * Experience with data visualization tools (Tableau, Looker) * Experience with Docker Containers * Excellent communication and storytelling skills * Experience with MLOps, model deployment, and version control (Git) [preferred] * Knowledge of natural language processing (NLP) or deep learning techniques * Exposure to semantic layer design and data governance frameworks