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 More ❯
deploy Machine Learning capabilities and techniques into other systems. Familiarity with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn. Commitment to writing clean, reusable, maintainable and well-tested code. Proficiency in automation, system monitoring, and cloud-native applications, with More ❯
stack Excellent communication and stakeholder management skills Nice to have Familiarity with the AWS environment (S3, Athena, Redshift) Experience with Python (Airflow, dbt, pySpark, Pandas) Experience with Snowflake Experience with Thoughtspot Familiarity with the command line Some understanding of Kafka Master's degree or equivalent in a quantitative field Previous More ❯
large datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience More ❯
large datasets. Ability to apply statistical techniques to validate models and algorithms. Data Manipulation & Analysis: Proficient in data manipulation and analysis using tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau to communicate insights effectively. Our offer: Cash: Depends on experience. More ❯
Woking, Surrey, United Kingdom Hybrid / WFH Options
Arrow McLaren IndyCar
and oral English language. Desirable Experience developing systems with Kafka and stream processing techniques. Experience with Linux and running containers on Kubernetes. Experience with pandas, numpy, SciKit, and other analytical packages. Experience designing distributed microservice based architectures. Strong background in mathematics, statistics, or mechanical engineering. Experience with QT Python thick More ❯
etc.). Attributes: Need to Haves: C++ - Strong understanding of multithreading, asynchronous programming, network protocols. Advanced knowledge of Python and related frameworks (FastAPI, NumPy, Pandas, Pydantic) including multithreading and parallel design principles. Understanding of AWS, including knowledge of Cognito, Pinpoint, IoT, MSK and other services. Deep understanding of user-centered More ❯
Machine Learning capabilities and techniques into other systems. Are familiar with the Python data science stack through exposure to libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn. Take pride in writing clean, reusable, maintainable and well-tested code. Demonstrate proficiency in automation, system monitoring, and cloud-native More ❯
set. Experience Required Essential A proven track record of programming in Python 3.x (up to latest version) and its supporting packages such as Numpy, Pandas, Multiprocessing and Scipy. A good understanding of programming in C++ and its Standard Template Library (STL). A fundamental understanding of software engineering subjects such More ❯
results in a complex environment by driving initiatives forward. What Would Make You Stand Out: Python code for testing and use of Python frameworks (Pandas, Numpy, Requests) Exposure to Code quality metrics, and shift-left principles Experience testing container resiliency (Docker/Kubernetes) Experience designing large end to end performance More ❯
Beam, TimeXtender, MS Fabric, etc. Implementing code that runs at a scale. Experience using Python and at least two libraries from the list: PySpark; Pandas/Dask; Numpy; Scikit-learn; Torch/Tensorflow/equivalent); Huggingface; Langchain. Experience owning, building and optimising data pipelines, CI/CD, and ETL processes. More ❯
to stakeholders across the business. Requirements: 4+ years of experience in Data Science, with a strong focus on AWS cloud solutions. Proficiency in Python (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch) and SQL . Hands-on experience with AWS services (SageMaker, Lambda, Glue, Redshift, Athena, S3). Strong understanding of ML More ❯
hands-on, with the opportunity to step into a leadership role as the team scales. Tech Stack - Python, FastAPI, AWS, Typescript, PostgreSQL, NumPy, Pandas What You’ll Be Doing - Designing, building, and maintaining scalable backend systems for AI-driven healthcare solutions. Working closely with the ML engineers to integrate AI More ❯
london, south east england, united kingdom Hybrid / WFH Options
Few&Far
hands-on, with the opportunity to step into a leadership role as the team scales. Tech Stack - Python, FastAPI, AWS, Typescript, PostgreSQL, NumPy, Pandas What You’ll Be Doing - Designing, building, and maintaining scalable backend systems for AI-driven healthcare solutions. Working closely with the ML engineers to integrate AI More ❯
MSc but open to others) 3+ years of commercial experience in data science Strong skills in probability, statistics, and mathematical modelling Proficiency in Python, Pandas, NumPy, SciPy, R, and other scientific computing tools Experience implementing data-driven solutions in a production environment Hands-on expertise with statistical modelling, feature engineering More ❯
and the ability to deliver high-quality results in complex environments. Bonus skills that’ll make you stand out: Python expertise with frameworks like Pandas and NumPy . Knowledge of Kafka , Kubernetes , and containerized application testing. Experience in performance validation and testing within CI pipelines. Familiarity with financial services or More ❯
must Strong programming skills as evidenced by earlier work in data science or software engineering, including experience with standard libraries for data science (NumPy, Pandas, Scikit-Learn etc). Generalist expertise across the entire data lifecycle including data strategy, data governance, risk and ethics, architecture, modelling. Technology implementation including data More ❯
understanding and hands-on experience with evaluation techniques in object detection and classification. Programming Skills: Language: Python Frameworks and libraries: Core python libraries like pandas, numpy, opencv, scikit-learn etc. Pytorch, Keras, Tensorflow, MMdetection (and other common CV libraries). Huggingface. Streamlit (or other alternatives). Cloud Technologies: AWS and More ❯
eager to explore, a diverse range of technologies including programming languages like Python and SQL; data processing libraries such as PySpark, Tidyverse, SparkR, and Pandas; platforms like Databricks and Posit; engineering tools including GitHub, AWS, Terraform, and DBT; and data visualization tools such as Power BI. You have hands-on More ❯
understanding and hands-on experience with evaluation techniques in object detection and classification Programming Skills Language: Python Frameworks and libraries: Core python libraries like pandas, numpy, opencv, scikit-learn etc Pytorch, Keras, Tensorflow, MMdetection (and other common CV libraries) Huggingface Streamlit (or other alternatives) Cloud Technologies: AWS Knowledge of appropriate More ❯
of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn Tooling & Environment: DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and More ❯
of how they work Python: You have built and deployed production-grade Python applications and you are familiar with data science libraries such as pandas and scikit-learn DevOps: You have experience working with DevOps tooling, such as gitops, Kubernetes, CI/CD tools (we use buildkite) and Docker Cloud More ❯
on hyper-scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., NumPy, SciPy, Pandas, PyTorch, JAX), especially including deep learning applications; C/C++ for computer vision, geometry processing, or scientific computing; software engineering concepts and best practices (e.g. More ❯
is highly advantageous. Technical Skills Programming Languages: Strong proficiency in Python, R, and SQL. Familiarity with Spark. Data Manipulation & Analysis: Experience with libraries like Pandas, NumPy, and Scikit-learn for data cleaning, manipulation, and model building. Machine Learning & Statistical Modeling: Solid understanding of supervised and unsupervised learning, feature engineering, model More ❯
