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Develop models leveraging statistical analysis, regression modeling, optimization, predictive modeling, simulation, machine learning, economic models. Knowledge of analytical models, methods, applications and tools, such as statistical analysis, regression modeling, predictive modeling, simulation, machine learning and selecting and applying the right analytical techniques.
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Proficient in data modeling, statistical analysis, and predictive modeling techniques, alongside a strong understanding of data visualization best practices and design principles. Proficiency in data modeling principles and techniques, statistical analysis, and predictive modeling techniques.
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Proving specialization background in data science, including experience with statistical analysis, data mining, predictive modeling, and machine learning; 6 year(s) of experience in data analytics with a focus on Ethics & Compliance is preferred.
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You will analyze a wide range of HR data, such as employee demographics, performance metrics, recruitment data, and employee surveys, using advanced statistical techniques and predictive modeling.
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Data Analysis and Modeling: You will work closely with the HR and People Analytics teams to understand their analytical needs and objectives. Overall, your role as an Advanced Analytics Lead in People Analytics is to leverage your expertise in advanced analytical methods to uncover meaningful insights from HR data.
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Advanced Analytics - Demonstrated proficiency in implementing advanced analytics solutions within Snowflake, including forecasting, predictive modeling and anomaly detection, leveraging Cortex AI.
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Experience with Python, R, SQL, and Predictive Modeling a plus. A well established consulting firm is seeking an FSA or ASA with a background in Predictive Modeling. Title: Predictive Modeling Actuary - Life.
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Bachelors degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics, or related Quantitative disciplines and 5+ years experience in predictive analytics or equivalent field.
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Demonstrated experience in one of the following domains: real-world data (EHR, insurance claims, registry data), building patient cohorts, enrollment modeling, clinical trial analytics. Experience delivering on Data Science projects using predictive technologies, forecasting, natural language processing, artificial intelligence, or machine learning.
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Expertise in statistical analysis, predictive modeling, machine learning and data mining techniques. The Associate Director – Commercial Data Science & Analytics will be responsible for leveraging data analytics techniques to drive business decisions and strategies; this requires a blend of technical expertise in data analytics, statistical modeling and machine learning along with strong business acumen.
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Qualifications Bachelor’s degree and 6+ years of experience or 8+ years of equivalent experience in data analytics or predictive modeling, preferably in a non-profit setting. Develop revenue reports, fundraising key performance indicator dashboards, and predictive analytics to drive donor acquisition and engagement strategies.
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Expert proficiency in SQL and experience with statistical modeling tools (R, Python) and common data science / ML approaches (e.g. Random Forest, Gradient Boosting and Logistic Regression, etc. Guide and direct analysts’ deep-dive advanced statistical and data science analyses (e.g. forecasting, predictive models, decision trees, classification, etc.
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Proficiency in data modeling and analysis tools such as Alteryx, Tableau, or related software, with experience in data manipulation, visualization, and predictive analytics to drive data-driven decision-making and identify actionable insights for process optimization.
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Solves business problems — Business to Consumer (B2C), Business to Business (B2B), quality operations, operations management, and automation — using Artificial Intelligence (AI) and data science techniques (Natural Language Processing (NLP), DL, ML, causal inference, predictive analytics, experimental design, and optimization.
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Employ deep learning, predictive analytics, time-series forecasting, and other AI methodologies to analyze and interpret large datasets, revealing valuable insights. Extensive experience in developing and deploying deep learning models, along with predictive analytics and time-series forecasting.
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predictive analytics modeling jobs in Boston, MA
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