1 to 25 of 83 Pandas Jobs in the City of London

working with Quant Trading Technology, and/or working with real-time Low Latency Market Data . Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

working with Quant Trading Technology, and/or working with real-time Low Latency Market Data . Expertise in Python, including popular Python libraries for data wrangling, such as Pandas, NumPy, and SQLAlchemy. Experience working with traditional SQL databases (e.g. PostgreSQL, MySQL, SQL Server) and cloud data warehouses (e.g. Snowflake, Databricks, BigQuery, Redshift). Experience with time-series data, and More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

alerting systems. Work closely with DevOps and infrastructure teams to deploy solutions in cloud and on-prem environments. Required Skills & Experience Strong proficiency in Python , including libraries such as Pandas, NumPy, and PySpark. Experience with data engineering tools (e.g., Airflow, Kafka, SQL, Parquet). Solid understanding of commodities markets , trading workflows, and financial instruments. Familiarity with cloud platforms (AWS, Azure More ❯

system performance • Implement robust risk management and stress-testing tools 🎯 What You Bring • 5+ years Java (OOP, low-latency systems) • 4+ years FX or Crypto trading experience • Python (NumPy, Pandas, SciPy) • SQL or time-series DBs • Linux & distributed systems expertise • Strong communication & market intuition ✨ Bonus Skills • KDB+/Q, Haskell, or other functional languages • Machine learning (scikit-learn, etc.) • Quant More ❯

alerting systems. Work closely with DevOps and infrastructure teams to deploy solutions in cloud and on-prem environments. Required Skills & Experience Strong proficiency in Python , including libraries such as Pandas, NumPy, and PySpark. Experience with data engineering tools (e.g., Airflow, Kafka, SQL, Parquet). Solid understanding of commodities markets , trading workflows, and financial instruments. Familiarity with cloud platforms (AWS, Azure More ❯

scalability of ML systems in production. What We’re Looking For 3+ years of experience in Data Science. Strong proficiency in Python and experience with ML libraries/frameworks (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Hands-on experience implementing end-to-end ML pipelines (data ingestion, training, validation, serving). Familiarity with ML workflow orchestration tools (Airflow, Prefect, Kubeflow More ❯

with at least 3+ years leading data science teams. Fluent in Python and a strong interest in general software engineering principles. You have worked with common python frameworks (Numpy, Pandas) Demonstrated expertise with agentic AI systems , including orchestration frameworks (LangGraph preferred, LangChain or similar also considered). Strong foundation in classical machine learning and applied modeling techniques , including regression, classification More ❯

and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯

and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯

learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes, MLflow More ❯

learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes, MLflow More ❯

data structures, algorithms, and software engineering best practices Track record of designing scalable, production-grade systems Excellent problem-solving, collaboration, and communication skills Nice to Have Experience with NumPy, Pandas, Cython, or Numba Exposure to market microstructure, risk modelling, or quantitative research Experience developing and maintaining live trading bots or algo execution systems Background in mentoring or technical leadership within More ❯

visualisation libraries (Matplotlib, Seaborn.) SQL for data extraction and manipulation. Experience working with large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for More ❯

particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to More ❯

particularly in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to More ❯

Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). More ❯

Proven experience (3–5+ years) as a Machine Learning Engineer , Data Scientist , or similar role. Strong programming skills in Python (experience with libraries such as TensorFlow, PyTorch, scikit-learn, pandas, NumPy). Solid understanding of machine learning algorithms , statistical modelling , and deep learning architectures . Hands-on experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, SageMaker, Vertex AI). More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

higher in computer science or equivalent Strong Python knowledge Strong interest and knowledge of financial markets and instruments Experience in data analysis techniques and libraries like NumPy, SciPy, and Pandas Solid understanding of mathematics, including statistics, asset pricing theory, and optimization algorithms More ❯

suggest new architecture and technologies to help shape the team going forward. What they are looking for: 3+ years of experience in Python, will consider C++. Ideally experience with Pandas and Numpy. Financial experience is preferred but not necessary. A strong Comp. Sci (or related degree) from a top university. Salary depends on experience. More ❯

higher in computer science or equivalent Strong Python knowledge Strong interest and knowledge of financial markets and instruments Experience in data analysis techniques and libraries like NumPy, SciPy, and Pandas Solid understanding of mathematics, including statistics, asset pricing theory, and optimization algorithms More ❯

Office platforms to provide enhances analytics and tooling for Traders and Front Office teams To be a successful applicant, you will need: Extensive experience of Software Engineering using Python (Pandas, Numpy, FastAPI) to a high standard, building highly performant systems and platforms used by Traders Experience working in a Hedge Fund, Trading firm, or similar working directly with front-office More ❯

Office platforms to provide enhances analytics and tooling for Traders and Front Office teams To be a successful applicant, you will need: Extensive experience of Software Engineering using Python (Pandas, Numpy, FastAPI) to a high standard, building highly performant systems and platforms used by Traders Experience working in a Hedge Fund, Trading firm, or similar working directly with front-office More ❯

phase of expansion. You'll be 100% hands-on, with the opportunity to step into a leadership role as the team scales. Tech Stack - Python, FastAPI, AWS, 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/ML models into More ❯