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The Data Science team is hiring an experienced Machine Learning Engineer with a background building machine learning and statistical modeling frameworks from scratch.
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Masters degree in Computer Science, Applied Mathematics, Data Science, Computational Physics/Chemistry or related technical subject area; PhD degree preferred. Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products.
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Bachelor's degree in Statistics, Computer Science, Mathematics, Machine Learning, Econometrics, Physics, Biostatistics or related Quantitative disciplines and 5 or more years experience in predictive analytics or equivalent.
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You have 2-5 years of successful technical experience in the domain of predictive analytics (e.g. data science, machine learning, data mining, and statistics related work); preferably in the Oil & Gas industry.
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As Data Scientist Lead - Risk Data and Analytics, you will be responsible for developing AI models using machine learning, deep learning, and natural language processing, particularly transformer models and Generative AI. Your expertise will be instrumental in developing and implementing predictive modeling solutions for the risk and compliance organization, enabling them to proactively identify and mitigate risks.
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This role demands a blend of expertise in data science and a deep understanding of the semiconductor industry, aiming to harness advanced data analytics, predictive modeling, and artificial intelligence to address complex business challenges.
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Lead team focused on new technologies such as process automation, complex predictive modeling, artificial intelligence, machine learning and computer vision to improve how we do business.
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8 years of experience in a predictive analytics or data analysis OR Advanced Degree (e.g., Master’s, PhD) in mathematics, computer science, statistics, economics, finance, actuarial sciences, science and engineering, or other similar quantitative field and 6 years of experience in predictive analytics or data analysis.
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Serves as a mentor to data scientists in modeling, analytics, computer science, discernment, and other interpersonal skills. 6 years proven experience in training and validating machine learning, statistical, physical, and other advanced analytics models.
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Experience in core data science and predictive analytics methods: Statistics (t-tests, Poisson process), Segmentation and clustering techniques, predictive modeling: e.g., regression, classification, Time Series analysis: e.g., ARIMA, Traditional machine learning methods: e.g., Random Forest, ensemble model techniques, Optimization: e.g. linear programming.
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Typical role includes working on a wide range of activities such as working with complex structured and unstructured datasets, developing/recommending novel machine learning tools, data visualizations, automation of analytics workflows, disease progression models, mechanistic and empirical PK/PD models, clinical trial simulations, literature meta-analysis using quantitative approaches and statistical modeling of historical and preclinical data.
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Scientific background in life sciences or engineering and demonstrated expertise in one or more of the following areas: data analytics, data visualization, statistics, machine learning, predictive modeling, decision analysis under uncertainty, artificial intelligence, Python and/or R, app development, and Tableau dashboard development.
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Knowledge of machine learning and AI methods and proficiency with scripting and executing data analytics algorithms and models with hands-on experience using a modeling and simulation software (e.g. Python, MATLAB, R, NONMEM, SAS, S-Plus, etc) is a must.
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Experience performing data science / analytics, such as statistical modelling, predictive analysis, or machine learning using Python, SQL, PySpark and cloud-based tools such as Big Query, Databricks.
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Develop machine learning models for forecasting, regression, classification, clustering, and advanced statistical analysis. Works with business and analytics leaders to prioritize analytics and highly complex modeling.
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machine learning predictive modeling analytics computer science jobs Company: Inc in Raleigh, West Virginia
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