1 to 25 of 52 Linear Algebra Jobs

for scalable AI deployments. Data Visualization : Proficiency in tools like Tableau, Power BI, and Python-based libraries such as Matplotlib, Seaborn, and Plotly. Statistics and Mathematics : Deep understanding of linear algebra, calculus, probability, and advanced statistical techniques. Soft Skills : Exceptional communication, critical thinking, and stakeholder management skills. Preferred Skills Familiarity with advanced ML techniques, such as reinforcement learning More ❯

Proven track record of developing and implementing successful AI-driven solutions, ideally within the financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication More ❯

Proven track record of developing and implementing successful AI-driven solutions, ideally within the financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication More ❯

quantitative researcher, quantitative analyst or another relevant role Degree in Applied Mathematics, Computer Science, Financial Engineering, Technology or Engineering Knowledge of probability theory, inferential statistics, machine learning, Bayesian statistics, linear algebra, and numerical methods Experience with statistical and machine learning models, such as regression-based models (e.g., logistic regression, linear regression, negative binomial regression), tree-based models More ❯

equivalent fields with one year of relevant work experience. - Excellent programming skills in Python. - Applied Machine Learning experience (regression and classification, supervised, and unsupervised learning). - Strong mathematical background (linear algebra, calculus, probability, and statistics). - Experience with scalable ML (MapReduce, streaming). - Ability to drive a project and work both independently and in a team. - Smart, motivated More ❯

Experience working in hybrid team structures, collaborating with contractors and external partners. Qualifications: A degree in a quantitative field (STEM Bachelor's/Master's) with strong foundations in Linear Algebra, Calculus, and Statistics, plus 2+ years as a Data Scientist. Alternatively, substantial industry experience combined with recognised certifications in Data Science demonstrating hands-on implementation. Why Join More ❯

in AI engineering, machine learning, or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to More ❯

in AI engineering, machine learning, or a similar role, preferably within the finance industry or at a leading technology company. Strong expertise in algorithms, data structures, multivariate calculus, and linear algebra. Proficient in Python, TensorFlow, PyTorch, or similar languages and frameworks, with experience writing CUDA kernels and profiling GPU code a plus. Excellent communication skills, with the ability to More ❯

i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming data structures, data mining, artificial intelligence). College-level requirement, or upper-level math … learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), 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. More ❯

i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming data structures, data mining, artificial intelligence). College-level requirement, or upper-level math … learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), 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. Clearance: Must Have an ACTIVE TS/SCI More ❯

i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming data structures, data mining, artificial intelligence). College-level requirement, or upper-level math … learning, data science, advanced analytical algorithms, programming (skill in at least on high level language (e.g. Python), 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. Position requires active Security Clearance with appropriate Polygraph More ❯

i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming data structures, data mining, artificial intelligence). College-level requirement, or upper-level math … learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python , 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. Experience in more than one area is strongly More ❯

i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming data structures, data mining, artificial intelligence). College-level requirement, or upper-level math … learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python , 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. Experience in more than one area is strongly More ❯

problems in an applied environment, and proficiency in critical thinking. Qualifications We Prefer Degree in Data Science, Machine Learning, Computer Science, Engineering, Statistics, or equivalent fields Strong mathematical background (linear algebra, calculus, probability & statistics) Experience with machine learning model training and analysis through open-source frameworks (Pytorch, Tensorflow, Sklearn) Experience crafting, conducting, analyzing, and interpreting experiments and investigations. More ❯

other groups. Required qualifications, capabilities, and skills Formal training or certification on software engineering concepts and advanced applied experience. Experience in statistical inference and experimental design (such as probability, linear algebra, calculus). Data wrangling: understanding complex datasets, cleaning, reshaping, and joining messy datasets using Python. Practical expertise and work experience with ML projects, both supervised and unsupervised. More ❯

learning, data science, advanced analytical algorithms, programming (skill in at least one high- level language (e.g. Python , 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. Experience in more than one area is strongly … i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, data structures, data mining, artificial intelligence). Military or applicable government work experience in More ❯

learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g., Python , 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. • Utilize analytic modeling, statistical analysis, programming, and/… learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language ( e.g., Python), 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. • Bachelor's Degree in Mathematics, Applied Mathematics Statistics … i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence) • Degree and minimum years of relevant work experience More ❯

learning, data science, advanced analytical algorithms, programming (skill in at least on high level language ( e.g. Python), 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. Bachelor's Degree must be in Mathematics, Applied … i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming, data structures, data mining, artificial intelligence). Military or applicable government work experience in More ❯

behavioral, social, and life) may be considered if it includes a concentration of coursework (typically 5 or more courses) in advanced mathematics (typically 300 level or higher; such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g., algorithms, programming, data structures, data mining, artificial intelligence). College-level Algebra or other math More ❯

i.e. behavioral, social, or life) may be considered if it included a concentration of coursework (5 or more courses) in advanced Mathematics (typically 300 level or higher, such as linear algebra, probability and statistics, machine learning) and/or computer science (e.g. algorithms, programming data structures, data mining, artificial intelligence). College-level requirement, or upper-level math … learning, data science, advanced analytical algorithms, programming (skill in at least one high-level language (e.g. Python , 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. Experience in more than one area is strongly More ❯

and translating research into practical solutions for predictive analytics. Experience in solution design, architecting and outlining data analytics pipelines and flows. Advanced Mathematics skills including experience with Bayesian statistics, linear algebra and MVT calculus, advanced data modelling and algorithm design experience. Design and deployment experience using Tensor Flow, Spark ML, CNTK, Torch or Caffe. The perks A flexible More ❯

of Python and modern ML libraries like PyTorch, Tensorflow, or JAX. Ability to implement models from academic papers like ICML, ICLR, NeurIPS, etc. Strong quantitative intuition and mastery of linear algebra, probability and statistics. Solid knowledge of basic data structures (list, vector, stack, heap), basic algorithms (sort, search, etc.) and associated time/memory asymptotic complexity. Maybe you More ❯

Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Mathematics skills to support the above: calculus, probability theory and linear algebra. Desirable Experience in one or more of: distributed computing, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other More ❯

Familiar with deep learning fundamentals: models, optimisation, evaluation and scaling. Capable of designing, executing and reporting from ML experiments. Mathematics skills to support the above: calculus, probability theory and linear algebra. Desirable Experience in one or more of: distributed computing, efficient computing based on low-precision arithmetic, deep learning models including large generative models for language, vision and other More ❯

video security use cases, and convert those ideas to working code. Requirements You should be a good software engineer who enjoys writing production-grade software. Strong machine learning fundamentals (linear algebra, probability and statistics, supervised and self-supervised learning). Keeping up with the latest in deep learning research, reading research papers, and familiarity with the latest developments More ❯