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Master's Degree in related field (e.g., Data Science, Predictive Analytics, Machine Learning, Statistics, Applied Mathematics, Computer Science) Bachelor's Degree in related field (e.g. Data Science, Predictive Analytics, Statistics, Marketing Analytics, Applied Mathematics, IT.
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Expertise in open source data science technologies such as Python, R, Spark, SQL. 5+ years of experience using AI/ML , data science software (e.g., Python-based tools) The Senior AI Engineer will have a strong technical background and demonstrated experiences in Gen AI, Data Science and AI/ML. The ideal candidate will be responsible for delivery of analytical models and AI solutions.
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Contribute towards advancing the AI Engineering and Data Science discipline in Ford Pro through the Community of Practice, including but not limited to driving data best practices, improving analytical processes, scaling knowledge and tools, and mentoring other data scientists.
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Expert level of Advanced and Predictive Analytical Methods e.g., Simulation, Design of Experiments, Genetic Algorithms, Ensemble Methods, Naïve Bayes, Neural Networks, regression, image processing, natural language processing.
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Ability to design and implement end-to-end machine learning pipelines for data ingestion, processing, modeling, and deployment. Knowledge of data preprocessing, feature engineering, and model evaluation techniques in machine learning projects.
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Proficiency in programming languages such as Python for data manipulation, analysis, and model development. 2+ years of experience in Automotive, Transportation, Digital Business, or Analytics Consulting.
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You will use your business acumen, knowledge of data and AI to support key products within Pro Tech that focus on improving customer experience, increasing revenue, and improving efficiency across the business.
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As ABSC’s Data Scientist , your job will be to perform cutting edge data analytics and support a major program advancing the state of the art in mission-focused big data analytics and predictive analytics.
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Master's degree (or higher) (or foreign education equivalent) in Engineering, Statistics, Data Science or a related field plus one (1) year of experience as a Data Analyst or a related occupation performing advanced analytics using predictive modeling and machine learning algorithms.
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Academic Backgrounds Preferred: Data Science, Statistics, Applied Math, Computer Science/Computer Information Systems, Operations Research, Economics, Environmental Engineering/Science, Computational Physics or other analytics degree.
$55,300 - $99,600 a yearFull-timeExpandApply NowActive JobUpdated 4 days ago - UpvoteDownvoteShare Job
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Walmart Connect is seeking an experienced data science leader to enable deep insights and capabilities to our clients through advanced analytics and machine learning techniques (e.g. predictive modeling, optimization, segmentation.
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8+ years post academic professional experience in data science, measurement, marketing strategy & analytics. Data science, machine learning, optimization models, PhD in Machine Learning, Computer Science, Information Technology, Operations Research, Statistics, Applied Mathematics, Econometrics, Successful completion of one or more assessments in Python, Spark, Scala, or R, Supervisory experience, Using open source frameworks (for example, scikit learn, tensorflow, torch.
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Swish Analytics is a sports analytics, betting and fantasy startup building the next generation of predictive sports analytics data products. Experience working with cross functional teams (Data Science teams a plus.
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With strong project portfolioMinimum 5 years of industry experience (2 years with PhD and 3 years with MS) in quantitative modeling of credit riskStrong quantitative/statistical skills in the field of predictive analytics with broad knowledge of regression analysis, time series analysis, Monte Carlo simulations, artificial intelligence, and data mining algorithmsExperience with modeling financial products and/or securitization, preferably mortgage-backed securities.
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Our high-performing team works with clients to implement the full spectrum of data analytics and data science, from data architecture and storage to data engineering and querying, to data visualization and dashboarding, to predictive analytics, machine learning, and artificial intelligence.
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