and risk analysis projects. Drive innovation and resource efficiency, contributing to the continuous development of their consulting offering and analytical capabilities as the company grows. Skills & Experience Python (incl. pandas, numpy, fastapi, dash/plotly) Database development: e.g. SQL, PostgreSQL, SQLAlchemy, data warehousing, ETL pipelines Cloud computing & DevOps: e.g. AWS (EC2, Lambda, S3), Docker, CI/CD, serverless architecture Frontend More ❯
years of professional software development with exposure to capital markets or trading (equities and/or execution). Technical Skills: Proficient in Python with some exposure to data analysis (Pandas, NumPy) or similar (R, MATLAB). Solid background in object-oriented programming (Java preferred; C++ or C# also valued). Familiarity with Linux-based systems (configuration, scripting, deployment). Docker More ❯
a technical and non-technical audience Independent and self-driven learner, able to step outside of their area of expertise Python; we work with asyncio, SQLAlchemy, FastAPI, Pydantic, NumPy, Pandas SQL; performance tuning, schema design, monitoring in production, we mainly work with PostgreSQL Cloud (AWS) deployments and monitoring, basic networking and security best practices Command line familiarity, git, automated testing More ❯
of established Quant Analytics team. What You Will Bring • University degree or equivalent with proven and displayed competency in data interrogation. • Strong proficiency and experience in Python (e.g., NumPy, pandas, scikit-learn) and quantitative thinking - you enjoy working with data to unearth patterns, trends, and nuances. • Exceptional analytical, problem-solving, and communication skills, with the ability to translate and present More ❯
Query Language (SQL) with a good understanding of best practices in software engineering and data engineering • Practical object-oriented programming experience in Python with knowledge of relevant packages including Pandas, NumPy, SciPy, Matplotlib, Scikit-learn, Pytorch • In-depth knowledge of statistical and machine learning models as well as experience with end-to-end delivery lifecycles • Experience in writing clean and More ❯
Strong analysis skills, proficiency with Excel and Python, SQL. Knowledge of agile methodologies/principles is a plus. Working knowledge and comfort level in using Python (inc. Numpy/Pandas) for data analysis. Job Responsibilities: Carry out data analysis using SQL (and Python as needed) for future feature requests. Support day to day application related issues/queries from users. More ❯
years of professional software development with exposure to capital markets or trading (equities and/or execution). Technical Skills: Proficient in Python with some exposure to data analysis (Pandas, NumPy) or similar (R, MATLAB). Solid background in object-oriented programming (Java preferred; C++ or C# also valued). Familiarity with Linux-based systems (configuration, scripting, deployment). Docker More ❯
that power the research, implementation and monitoring of their trading pipelines. Amazon S3 serves as our primary data storage solution, and we make heavy use of Python libraries (e.g. Pandas) for data manipulation. We are increasingly making use of cloud-based solutions to provide on-demand resource scaling to satisfy burstable strategy workloads, and as such utilise Docker containerisation for More ❯
training: Prior experience working for a data product company Experience building or maintaining third-party or in-house data quality and cataloguing solutions Experience with documentation of system architecture Pandas, Jupyter, Plotly DBT, Kafka BI tools such as Tableau, Metabase and Superset The current tech stack: Airflow Clickhouse DBT Python MongoDB PostgreSQL MariaDB Kafka K8s AWS FXC Intelligence is a More ❯
language modelling, and semantic similarity. Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar. Experience with data science tools and platforms (e.g., Jupyter, Pandas, NumPy, MLFlow). Familiarity with cloud-based AI tools and infrastructure, especially within the AWS ecosystem (SageMaker, Lambda, etc.). Strong understanding of data structures, algorithms, and statistical analysis. Experience More ❯
particular asset class or market sector. Our systems are almost all running on Linux and most of our 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. Inclusion, Work-Life Balance and Benefits at Man Group You'll thrive in our working environment More ❯
the adoption of best practices in data science across the organisation, lead other data science engineers MINIMUM QUALIFICATIONS Industry experience using Python for data science (e.g. numpy, scipy, scikit, pandas, etc.) and SQL or other languages for relational databases. Experience with a cloud platform such as (AWS, GCP, Azure etc.) Experience with common data science tools; statistical analysis, mathematical modelling More ❯
Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with More ❯
Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with More ❯
with experience building complex, maintainable systems Professional software development experience with a track record of delivering high-quality, production-grade code Experience with scientific computing libraries such as NumPy, Pandas, or SciPy in production environments Holistic software development mindset covering testing, documentation, security, and performance Track record of mentoring other engineers and sharing knowledge across teams Working knowledge of mathematical More ❯
features end-to-end, from ideation to deployment. Be on-call for urgent AI model fixes or system failures. Qualifications Proficiency in Python and related libraries (e.g., NumPy, SciPy, pandas) is required. Strong production experience with at least one framework: LangChain, AutoGen, or CrewAI. Deep understanding of agentic systems, autonomous workflows, and LLM-based automation. Experience deploying and fine-tuning More ❯
Query Language (SQL) with a good understanding of best practices in software engineering and data engineering • Practical object-oriented programming experience in Python with knowledge of relevant packages including Pandas, NumPy, SciPy, Matplotlib, Scikit-learn • In-depth knowledge of statistical and machine learning models • Experience in writing clean and maintainable code for collaborative working and using code versioning tools • Excellent More ❯
the adoption of best practices in data science across the organisation, mentor other data science engineers. MINIMUM QUALIFICATIONS Industry experience using Python for data science (e.g. numpy, scipy, scikit, pandas, etc.) and SQL or other languages for relational databases. Experience with a cloud platform such as (AWS, GCP, Azure etc.). Experience with common data science tools; statistical analysis, mathematical More ❯
with experience building complex, maintainable systems Professional software development experience with a track record of delivering high-quality, production-grade code Experience with scientific computing libraries such as NumPy, Pandas, or SciPy in production environments Holistic software development mindset covering testing, documentation, security, and performance Track record of mentoring other engineers and sharing knowledge across teams Desirable: Working knowledge of More ❯
degree in Computer Science, Engineering, or a related field 1–3 years of experience in software development or process automation Proficiency in Python, with experience using libraries such as Pandas, Requests, or Selenium Familiarity with SQL and working with relational databases Strong problem-solving skills and attention to detail Effective communication skills and a collaborative mindset Experience with REST APIs More ❯
Query Language (SQL) with a good understanding of best practices in software engineering and data engineering Practical object-oriented programming experience in Python with knowledge of relevant packages including Pandas, NumPy, SciPy, Matplotlib, Scikit-learn, Pytorch In-depth knowledge of statistical and machine learning models as well as experience with end-to-end delivery lifecycles Experience in writing clean and More ❯
London, England, United Kingdom Hybrid / WFH Options
Plentific
work with Python and Django on an increasingly more service-oriented architecture. The rest of the tech stack include Django REST Framework, PostgreSQL, AWS, React.js, Kubernetes, Docker, Redis, Celery, Pandas, Numpy, Git, Jenkins and Elasticsearch. We have a very large but clean code base as we put significant emphasis on design patterns, code readability, automated testing, maintainability and extendability. Responsibilities More ❯
Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark, or Kafka. Strong understanding of SQL, NoSQL, and data modeling. Familiarity with More ❯
London, England, United Kingdom Hybrid / WFH Options
NATO
practical experience. • Professional software development experience using languages such as Python, C, Julia, C++, or similar. • Strong proficiency in Python and its scientific computing/ML ecosystem (e.g., NumPy, Pandas, TensorFlow, AI Foundry, OpenAI, Scikit-learn etc.). • Solid understanding of core machine learning concepts • Hands-on experience with at least one major deep learning framework (e.g., TensorFlow, PyTorch, Keras More ❯
