Credit Rates Bonds ABS Vue Angular React Agile AWS GCP Buy Side Asset Manager Investment Management Performance Risk Attribution TypeScript Node Finance Front Office Trading Financial Services Pandas Numpy Scipy) required by our asset management client in London. You will join a team of 4 that is responsible for an in-house built order tracking and communication platform. It will More ❯
pipeline from scouting to trading. Our Technology Our systems are almost all running on Linux and most of our code is in Python, with the full scientific stack: numpy, scipy, pandas to name a few of the libraries we use extensively. We implement the systems that require the highest data throughput in Java. Within Data Engineering we use Dataiku, Snowflake … languages Working knowledge of one or more relevant database technologies e.g. MongoDB, PostgreSQL, Snowflake, Oracle Proficient with a range of open source frameworks and development tools e.g. NumPy/SciPy/Pandas, Spark, Jupyter Advantageous Prior experience of working with financial market data or alternative data Relevant mathematical knowledge e.g. statistics, time-series analysis Experience in data visualisation and building More ❯
the ability to deliver timely solutions to Portfolio and Risk Managers Required Skills/Experience Minimum 5 years of experience using Python and scientific python libraries (e.g., pandas, NumpPy, SciPy). Strong understanding of cloud infrastructure and experience working with cloud services (e.g., AWS, Azure, or GCP). Prior experience in system design and data modeling, with the ability to More ❯
financial products. Deep understanding of financial mathematics, statistical analysis, and machine learning as applied to financial markets. Strong Python development skills, including proficiency with libraries such as NumPy, Pandas, SciPy, and machine learning frameworks. Java experience is a bonus. Proficiency with time-series databases, modern version control, and CI/CD pipelines. Familiarity with cloud-based technologies and scalable system More ❯
Degree in Computer Science, Math, Physics, Engineering, or related quantitative field. Minimum of 2+ years of Python developer proficiency with quantitative analysis experience with packages such as numpy, pandas, scipy, scikitlearn, matplotlib, etc. Proficiency in Linux environment (including shell scripting). 1+ years of experience with automation frameworks in software testing (e.g., PyTest, Cucumber). Experience and/or technical More ❯
Within Risk Engineering we run a mixture of Linux and Windows, and use Python as the primary language, with an emphasis on Python and the Python scientific stack: numpy, scipy, pandas, scikit-learn, etc. We implement the systems that require the highest data throughput in Java. We implement most of our long running services and analytics in C#. We use More ❯
a good working knowledge of statistics. The Technology Systems are almost all running on Linux and most of the code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the open-source libraries we use extensively. We implement the systems that require the highest data throughput in Java and C++. We … C++ desirable) Experience of the challenges of dealing with large data sets, both structured and unstructured Used a range of open source frameworks and development tools, e.g. NumPy/SciPy/Pandas, Spark, Kafka, Flink Working knowledge of one or more relevant database technologies, e.g. Oracle, Postgres, MongoDB, ArcticDB. Proficient on Linux Advantageous: An excellent understanding of financial markets and More ❯
quality for thousands of datasets in use across the firm. Their core systems almost all run on Linux and most code is in Python, including extensive use of numpy, scipy, pandas, scikit-learn, etc. Systems that require the highest data throughput are implemented in Java, and they use Dataiku, Snowflake, Prometheus, and ArcticDB heavily. New tools and libraries are constantly More ❯
degree in Statistics, Applied Maths, Physics or related field. Minimum of 2 years working in a Data Science related role Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Hartree Partners
related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯
related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯
South East London, England, United Kingdom Hybrid / WFH Options
Hartree Partners
related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow, dbt) Track record More ❯
and implementing data science and machine learning solutions to tackle business problems. Comfort with rapid prototyping and disciplined software development processes. Experience with Python, ML libraries (e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi-disciplinary teams More ❯
London, England, United Kingdom Hybrid / WFH Options
EDF Trading Ltd
with data visualization tools e.g. PowerBI or Tableau Data extraction and manipulation languages e.g. SQL, Python Knowledge of statistical software and packages such as R, Matlab, Pandas, NumPy or SciPy Experience with algorithmic trading systems and low-latency trading Knowledge of financial markets is desirable but experience of working in other "big data" or HPC environments is equally valid. Hours More ❯
Risk Engineering we run a mixture of Linux and Windows, and use Python and C# as primary languages, with an emphasis on Python and the Python scientific stack: numpy, scipy, pandas, scikit-learn, etc. We implement the systems that require the highest data throughput in Java. We implement most of our long running services and analytics in C#. We use More ❯
to client pricing and flow analysis. At least 5 years of advanced Java development experience, including: Strong understanding of object-oriented programming and design patterns. Proficiency in Python (NumPy, SciPy, Pandas) for data analysis and prototyping. Experience with SQL and/or time-series databases. Strong Linux skills and experience working in globally distributed environments. Solid understanding of financial markets … years of advanced Java development experience, including: Strong understanding of object-oriented programming and design patterns. Proven experience building high-performance, low-latency systems. Proficiency in Python (NumPy, SciPy, Pandas) for data analysis and prototyping. Experience with SQL and/or time-series databases. Strong Linux skills and experience working in globally distributed environments. Solid understanding of financial markets and … years of advanced Java development experience, including: * Strong understanding of object-oriented programming and design patterns. * Proven experience building high-performance, low-latency systems. * Proficiency in Python (NumPy, SciPy, Pandas) for data analysis and prototyping. * Experience with SQL and/or time-series databases. * Strong Linux skills and experience working in globally distributed environments. * Solid understanding of financial markets and More ❯
which until recently were considered impossible, or extremely difficult, to solve. Their core systems run on Linux and most code is written in Python, including extensive use of numpy, scipy, pandas, scikit-learn, etc. But they’re also constantly evaluating new technologies, tools and libraries, meaning you can shape the technology landscape and make an impact early on. Requirements Passion … for AI engineering, someone who stays up to date with major advancement in AI tools and models Strong development knowledge of Python Experience of data analysis techniques, plus numpy, scipy, pandas, etc. Solid Linux platforms experience with various scripting languages Proponent of collaborative software engineering techniques and agile methods Degree with high mathematical and computing content – Computer Science, Mathematics, Engineering More ❯
or extremely difficult to solve. The Technology Core systems are almost all running on Linux and most of the code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the libraries used extensively. For storage, they rely heavily on MongoDB. They use Docker, Kubernetes and Airflow to streamline deployments and leverage … C++ desirable) Experience of the challenges of dealing with large data sets, both structured and unstructured Used a range of open source frameworks and development tools, e.g. NumPy/SciPy/Pandas, Spark, Kafka, Flink Working knowledge of one or more relevant database technologies, e.g. Oracle, Postgres, MongoDB, ArcticDB. Proficient on Linux Advantageous: An excellent understanding of financial markets and More ❯
City of London, London, United Kingdom Hybrid / WFH Options
SGI
Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯
Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯
South East London, England, United Kingdom Hybrid / WFH Options
SGI
Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast-paced front More ❯
Requirements 3+ years’ software engineering experience, where Python is your main language Bachelor’s degree in Computer Science or Engineering (or related field) Substantial experience with Python libraries: numpy, scipy, pandas, matplotlib, sklearn, etc. Passion for building clean, reliable and maintainable software Strong quantitative reasoning skills Highly skilled at multitasking and time management in a fast-paced environment Market-leading More ❯
written and verbal Bonus Points: Experience of research and backtesting to evaluate the performance of trading strategies and models Proficiency in Rust and Python, statistical tools (e.g., NumPy, pandas, SciPy) Experience of development with relational and time series database technologies Knowledge of risk management infrastructure What We Offer: Competitive base salary and discretionary bonus Company-paid health and protective benefits More ❯
and implementing data science and machine learning solutions to tackle business problems. Comfort with rapid prototyping and disciplined software development processes. Experience with Python, ML libraries (e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi-disciplinary teams More ❯
