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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.
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A Research Scientist at Numerica should possess an M.S. or Ph. D. in Applied or Computational Mathematics, Electrical Engineering, Computer Science, Controls and Dynamical Systems, Aerospace Engineering, Statistics and Probability, or a related field.
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Our areas of expertise include remote sensing, geospatial analysis, GIS, soil science, water quality and demand evaluation, agricultural systems, salinity and nutrient management, ecosystem restoration, statistics, and regulatory policy.
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Business Intelligence (BI), Database Design, Data Engineering, Data Modeling, Data Science, Data Visualization, Machine Learning, Project Management, Software Development, Stakeholder Relationship Management.
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Ph. D (preferred), Bachelor's or Master's degree in Computer Science, Mathematics or Statistics , Computational linguistics, Engineering, or a related field. You will be instrumental in leading strategic direction for ML, NLP, LLM, algorithm development in a world class AI ML team while working alongside well-known experts and researchers in AI ML modeling, ML engineers and data science and data engineering teams.
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Land IQ, LLC is seeking a Remote Sensing Scientist in its Sacramento, California office with a specialization in data driven analytics and algorithm development with digital images for agricultural and other land use applications (crop classification, yield modeling, land use impacts, land use change, etc.
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Bachelors degree in Mathematics, Statistics, Engineering, Social/Physical/Life Science, Business, or related field and Minimum five (5) years experience in data analytics or a directly related field.
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Actuarial Science, Statistics, Mathematical Statistics, Applied Mathematics, Mathematics, Economics, Engineering. Certification requirements may be waived if the candidate has more experience in the relevant modeling and product valuation fields.
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Masters’ degree in data science, computational linguistics, data mining, machine learning, statistics, computer science, operations research, engineering, mathematics or related field required. 5 years of demonstrated success conducting predictive modeling, data science, and analysis projects required.
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Experience or exposure related to the following topic areas (note that experience in all these areas is not required) Topic Areas: Field work, traffic operations analysis, signal design, transportation planning (e.g., bicycle or transit plans, infrastructure finance, transportation and land use policy, and/or travel demand modeling.
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The day-to-day: As a Data Scientist you will utilize experience in designing/implementing machine learning, data science, advanced analytical algorithms, programming (skill in at least one high level language (e.g. Python), statistical analysis, variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering.
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Statistical analysis (e.g. variability, sampling error, inference, hypothesis testing, EDA, application of linear models), data management (e.g. data cleaning and transformation), data mining, data modeling and assessment, artificial intelligence, and/or software engineering.
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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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Knowledge of Machine Learning, Data Mining, Statistics, Applied Mathematics, or a related field. 2+ years of experience in machine learning with domain knowledge and experience in the following areas: data-driven statistical modeling, discrimination methods, feature extraction and analysis, supervised learning.
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Bachelor's degree in Data Science, Statistics, Mathematics, Computer Science or other quantitative field. Master’s degree or greater in Statistics, Mathematics, Computer Science or other quantitative field; or equivalent working experience.
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