Python and its ecosystems; experience with other languages is a plus Ability to deploy ML capabilities into systems Familiarity with Python data science libraries (NumPy, SciPy, Pandas, Dask, spaCy, NLTK, scikit-learn) Commitment to writing clean, maintainable, and well-tested code Proficiency in automation, system monitoring, and cloud platforms like More ❯
understanding of computer systems and how they operate. Excellent Python programming skills, including experience with relevant analytical and machine learning libraries (e.g., pandas, polars, numpy, sklearn, TensorFlow/Keras, PyTorch, etc.), in addition to visualization and API libraries (matplotlib, plotly, streamlit, Flask, etc). Experience developing and implementing quantitative models More ❯
of software development experience in quantitative trading, with deep expertise in Java and/or Python. Proficient in Python's data science ecosystem (Pandas, NumPy, Scikit-learn), with strong debugging and analytical skills. Proven track record implementing trading algorithms and working with distributed systems in fast-paced front-office environments. More ❯
organized, demonstrating thoroughness and strong ownership of work Desirable skills/experience: Experience working with python, and data analysis libraries (pandas/polars/numpy) Experience with financial mathematics, statistics, and broad understanding of financial services/instruments Experience in JavaScript development, especially in AngularJS or ReactJS AWS cloud services More ❯
Desired Skills and Experience: Kafka and message bus/queue expertise Kubernetes knowledge Terraform and GitHub Actions skills Open Telemetry (OTEL) implementation Proficiency with NumPy and Pandas Systems integration experience Background in commodity trading (gas & power) Quantitative finance knowledge Understanding of compliance and regulation, particularly Sarbanes-Oxley (SOx) Role Responsibilities More ❯
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 Equity More ❯
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 Equity More ❯
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 More ❯
technology and client needs shift. Role Requirements Technical Skills Substantial experience in data engineering, analytics engineering, or similar roles. Hands-on expertise with Python (Numpy/Pandas) and SQL. Proven experience designing and building robust ETL/ELT pipelines (dbt, Airflow). Strong knowledge of data pipelining, schema design, and More ❯
such as MLflow, AWS Sagemaker, and Azure Machine Learning Experience in relevant Data Manipulation, Machine Learning and Statistical Analysis coding packages (eg. in Python: NumPy, Scikit-Learn, Pandas, Matplotlib etc.) Strong skills in data exploration, cleansing, modelling and presentation Strong experience in testing data models and Machine Learning Models Strong More ❯
and intuitive UX Strong grounding in best practices of software development Professional experience with python Proficiency with common data science libraries such as pandas, numpy and scipy Comfortable with quickly evolving requirements Additional Valuable Skills: Experience designing and building front end apps Understanding and appreciation of dev ops industry standards More ❯
Flakes) Data pipelines and big data tech Docker: both building but running too Wide AWS and infrastructure knowledge, including production support Scientific computing e.g. Numpy/scipy/pandas Just state the word 'Salmon' anywhere in your application, just to prove you can read a job advert. We aim to More ❯
Flakes) Data pipelines and big data tech Docker: both building but running too Wide AWS and infrastructure knowledge, including production support Scientific computing e.g. Numpy/scipy/pandas Just state the word 'Salmon' anywhere in your application, just to prove you can read a job advert. We aim to More ❯
. You have strong analytical skills You can communicate about complex subjects to non-technical stakeholders You are familiar with Terraform , Python , Pandas , and NumPy It is great if you have: Experience with Neural Networks/Deep Learning. Experience with information extraction, parsing, and segmentation. Experience with machine learning frameworks More ❯
as hands-on experience on AWS services like SageMaker and Bedrock, and programming skills such as Python, R, SQL, Java, Julia, Scala, Spark/Numpy/Pandas/scikit, JavaScript. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need More ❯
efficiency and effectiveness. Technical Expertise: Advanced proficiency in Python with minimum demonstrable programming experience including data manipulation and analysis using libraries such as Pandas, NumPy, and SQLAlchemy. Extensive experience with Dash framework for building web applications. In-depth knowledge of Impala or other SQL-on-Hadoop query engines. Understanding of More ❯
and deploy 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 More ❯
Node.js, JavaScript (JS), and TypeScript (TS). Statistical Knowledge: Solid understanding of statistical concepts and methodologies. Data Manipulation & Analysis: Proficiency with tools like Pandas, NumPy, and Jupyter Notebooks. Experience with data visualization tools such as Matplotlib, Seaborn, or Tableau. More ❯
and even have the ability to be client facing! Requirements 5+ years experience with Data Engineering Strong working knowledge with Python/Pandas/NumPy/ETL pipelines Strong AWS experience (ideally Lambda & Step Functions) Beneficial: Experience or interest in the financial markets Experience in client facing role Previous start More ❯
judged by the ability to deliver timely solutions to portfolio and risk managers within the firm. Mandatory Requirements 3+ years Python development experience (pandas, numpy, polars, jupyter notebooks, FAST API) Experience with AWS services, such as: S3, EC2, AWS Batch and Redshift Proficiency in relational and non-relational database technologies More ❯
and even have the ability to be client facing! Requirements 5+ years experience with Data Engineering Strong working knowledge with Python/Pandas/NumPy/ETL pipelines Strong AWS experience (ideally Lambda & Step Functions) Beneficial: Experience or interest in the financial markets Experience in client facing role Previous start More ❯
of hands-on development experience in Python or another object-oriented programming language. Strong proficiency in Python’s data ecosystem, including libraries such as NumPy , Pandas , and Matplotlib . Experience working with cloud platforms (AWS preferred) and Infrastructure-as-Code tools. Solid understanding of relational databases and SQL. Proven track More ❯
of hands-on development experience in Python or another object-oriented programming language. Strong proficiency in Python’s data ecosystem, including libraries such as NumPy , Pandas , and Matplotlib . Experience working with cloud platforms (AWS preferred) and Infrastructure-as-Code tools. Solid understanding of relational databases and SQL. Proven track More ❯
priority. Development and maintenance of Continuous Integration (CI) pipelines. Complex deployments on AWS. Docker or comparable containerization technologies. Nice to have experience: Experience using numpy/pandas/torch/etc. Experience with Golang. Our salary range for the role is £70,000 to £130,000, depending on experience and More ❯
