1 to 25 of 29 Permanent Linear Algebra Jobs in London

experience developing, testing machine learning solutions using frameworks such as TensorFlow, PyTorch or scikit‐learn. Solid intuitive grasp of fundamental concepts from probability, statistics, linear algebra and calculus. Collaborative, humble and enthusiastic attitude. Preferred Qualifications, Capabilities and Skills Experience deploying on AWS cloud infrastructure using Lambda, Glue ...

LangGraph and/or Google ADK.Strong Python and SQL; able to write clean, production-ready code. Strong AI/ML fundamentals, including statistics, probability, linear algebra, and model evaluation. Experience with scikit-learn and either PyTorch or TensorFlow. Practical DevOps mindset: testing, CI/CD, reproducibility, code quality ...

/IP DNS NAT TLS/HTTPS Routing Load balancing Firewalls Congestion control Mathematics for Computing Logic Discrete maths Probability Statistics Graph theory Linear algebra Boolean algebra Combinatorics Proofs Number theory Distributed & Cloud Systems Replication Partitioning CAP theorem Event-driven architecture Idempotency Eventual consistency Queues & streams Serverless ...

Python are fundamental, alongside proficiency with ML frameworks like TensorFlow and PyTorch. Machine Learning Engineers need solid mathematics and statistics knowledge, particularly in linear algebra, calculus, and probability theory. Experience with cloud platforms (AWS, GCP, Azure) is essential for deploying models at scale. Skills in data preprocessing, feature ...

data pipelines and ETL processes, directly contributing to the team's delivery of secure and stable data architectures Applies advanced data modeling techniques, including linear algebra, statistics, and geometrical algorithms to solve real world business challenges and drive actionable insights Collaborates closely with cross-functional teams to integrate ...

equivalent in Quantitative Discipline (i.e. Finance, Statistics, Computer Science, Actuarial Science, Economics, Engineering etc.)Knowledge of advanced statistical concepts and techniques, e.g. skilled in linear algebra. Experience conducting hands-on analytics projects using advanced statistical methods such as generalized regression models, Bayesian methods, random forest, gradient boosting, neural networks ...

with natural language processing technology, including LLMs and prompt engineering is a plus Strong quantitative skills with demonstrated understanding of mathematics, probability, statistics and linear algebra Nuanced understanding of economic and financial concepts and demonstrated intuition around applying these concepts in a quantitative environment Ability to work independently ...

software engineering experience, with strong CS fundamentals (data structures, algorithms, systems design) Demonstrated mathematical maturity - comfort with the concepts and notation used in statistics, linear algebra, optimization, and probability Deep proficiency in Python; experience with R and/or C/C++ is a strong plus Extensive experience ...

build and make predictions with those models Strong understanding of machine learning approaches and algorithms Deep understanding of Statistical/Probabilistic programming and Linear Algebra Be an expert in (Python, R, SQL) programming for Data Science and Time Series analysis Have in depth understanding of statistical modelling/ ...

frameworks for building with large language models alongside libraries such as pandas, NumPy and scikit-learn. Strong mathematical and statistical foundations, including probability, statistics, linear algebra and optimization, and the ability to reason rigorously about uncertainty, error and model behavior. A sound grounding in machine learning, including model ...

cloud platforms (e.g., AWS, GCP, Azure) and data warehousing solutions. Strong knowledge in at least a few of the following areas: statistics, machine learning, linear algebra, optimisation. A strong product mindset with the ability to operate autonomously while working in a cross-functional and cross-team environment. Good ...

trust in the analysis they produce based on the data our product line emits. Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithms Delivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable way Implements database ...

problems. Advanced academic training in Statistics, Mathematics, Machine Learning, Data Science or a related discipline (PhD preferred). Deep understanding of probability, statistics, uncertainty, linear algebra and calculus. Extensive experience working with large datasets, data preparation and machine learning workflows. Proven experience applying classification, clustering, dimension reduction ...

problems. Advanced academic training in Statistics, Mathematics, Machine Learning, Data Science or a related discipline (PhD preferred). Deep understanding of probability, statistics, uncertainty, linear algebra and calculus. Extensive experience working with large datasets, data preparation and machine learning workflows. Proven experience applying classification, clustering, dimension reduction ...

risk with good understanding of risk modelling. Credit experience is preferred. Very good grasp and understanding of mathematical concepts like probability, statistics, stochastic calculus, linear algebra, Monte Carlo techniques. MSC in a related discipline Good knowledge of Python, SQL, Matlab, VBA. Good understating of financial products (Bonds, Derivatives ...

Python, R, or C/C++. Familiarly with data science toolkits, such as scikit-learn, PandasStrong command of foundations of applied and theoretical statistics, linear algebra, and machine learning techniquesCollaborative mindset with strong independent research abilitiesCommitment to the highest ethical standards ...

trust in the analysis they produce based on the data our product line emits. Generates data models for their team using firmwide tooling, linear algebra, statistics, and geometrical algorithmsDelivers data collection, storage, access, and analytics data platform solutions in a secure, stable, and scalable wayImplements database back ...

Electrical Engineering, Statistics, or equivalent fields. Applied AI experience (generative AI, agentic solutions, 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 projectand workbothindependently and in a team. ...

minimum of 2 years of commercial experience applying statistical modelling and machine learning techniques to real-world problems. Solid grounding in probability, statistics, uncertainty, linear algebra and calculus. Experience working with large datasets, data transformation and cleaning. Experience with classification, clustering, dimension reduction and other machine learning methods. ...

with experience in either computer vision, foundation models, or 3D medical imaging. Deep understanding of machine learning theory and its background, including deep learning, linear algebra, probability theory, statistics and optimisation. Strong Python and PyTorch skills, with the ability to work confidently in model training and inference codebases. ...

minimum of 2 years of commercial experience applying statistical modelling and machine learning techniques to real-world problems. Solid grounding in probability, statistics, uncertainty, linear algebra and calculus. Experience working with large datasets, data transformation and cleaning. Experience with classification, clustering, dimension reduction and other machine learning methods. ...

financial institutions, including global investment banks and multi-strategy hedge funds. Who will love this job A scientist – you are comfortable with numerical methods, linear algebra, partial differential equations, probability theory and statistics An engineer – who has a passion for computer science, system performance, clean code and architecture ...

financial institutions, including global investment banks and multi-strategy hedge funds. Who will love this job A scientist – you are comfortable with numerical methods, linear algebra, partial differential equations, probability theory and statistics An engineer – who has a passion for computer science, system performance, clean code and architecture ...

strong statistical foundation. Strong programming skills in Python, with the ability to develop efficient and scalable research tools. Solid understanding of applied statistics, linear algebra, and time series analysis. Experience working with large and complex datasets, including data cleaning, transformation, and analysis. Knowledge of financial markets ...

math, quantitative finance, or other quantitative fields with a strong foundation in statistics Demonstrated proficiency in Python Strong command of foundations of applied statistics, linear algebra, and time series models Ability to quickly and efficiently scrub, format, and manipulate large, raw data sources Knowledge of financial markets Highly ...