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The ideal candidate will have a solid background in machine learning and statistical modeling, The Lead AI/ML Engineer will play a key role in developing and implementing data-driven strategies to improve lead generation and lead scoring, customer segmentation, and marketing automation activities.
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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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1 year of experience with Python, R or other statistical analyst software. Develop and execute validation testing for statistical, econometric, and machine learning models used in loss forecasting, allowance and stress testing for retail portfolios.
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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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Expertise in machine learning, statistical analysis, and predictive modeling (5 years) Expertise in at least one programming language used for data analysis (eg Python, R) (7 years.
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Data Analysis: Analyze client data to uncover insights, identify trends, and develop actionable recommendations, using statistical analysis techniques, machine learning algorithms, and data visualization tools.
$150,000 - $200,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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Perform data exploration using a combination of statistical programming languages (including, but not limited R, Python, SQL, SAS) and deploy predictive analytics and machine learning techniques to improve risk prediction, improve reserve, trend and financial forecasting in a manner that is actuarially sound, and enable real-time results and operational efficiencies.
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You understand the data science lifecycle and are experienced in development and implementation of advanced statistical models and machine learning algorithms. Experience evaluating, selecting, developing, and deploying statistical and machine learning models.
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Strong proficiency in programming languages such as Python, R, and TensorFlow/PyTorch. We are seeking a highly skilled and experienced Data Scientist with expertise in Generative AI to join our team in San Francisco, CA. The ideal candidate will have a strong background in data science, machine learning, and specifically generative AI techniques.
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Has advanced understanding, and can apply knowledge of, complex mathematical techniques (but not limited to): statistical outlier methods, logistic regression, natural language processing (NLP), and various machine learning methods (e.g., random forest, XGBoost, etc.
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Technical Proficiency: Familiarity with data science methodologies (machine learning, statistical modeling, etc.) and tools (Python, R, SQL, etc. KEY RESPONSIBILITIES: Team builder with an understanding of Generative AI use cases techniques including zero shot learning, fine tuning and RAG Project Leadership: Lead end-to-end project management for data science initiatives, from inception to completion, ensuring alignment with strategic goals and timelines.
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Expertise in statistical modeling, machine learning algorithms, and data mining techniques, with proficiency in programming languages such as Python, R, or SQL. Utilize advanced analytics, machine learning, and statistical modeling techniques to analyze large volumes of structured and unstructured data related to customer behavior, product trends, and digital commerce performance.
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Experience with machine learning, data mining, econometric modeling, and general statistical modeling. Strong programming skills in at least one language, such as Python, R, C.
$152,000 - $192,500 a yearExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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Construct and fit statistical, machine learning, or optimization models. Proficiency with Python, or another interpreted programming language like R or Matlab. Proficiency with Python, or another interpreted programming language like R or Matlab.
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Experience in the usage of machine learning/AI tools in life science area(s) and handling life science datasets is preferred. Adapt data science algorithms (supervised and unsupervised learning, decision trees, neural networks, AI based image processing and feature extraction, Bayesian learning, etc) for modeling clinical trial data to support drug development.
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