51 to 75 of 183 Pandas Jobs in London

version control processes. Stay up to date with advances in quantitative finance, computational techniques, and emerging technologies. Profile Strong programming experience in Python, C++, or C#; knowledge of NumPy, Pandas, and QuantLib advantageous. Solid understanding of mathematics, statistics, and numerical methods - including stochastic calculus, Monte Carlo simulation, and optimisation. Familiarity with derivatives pricing, risk metrics, and financial instruments across asset More ❯

and pipelines. Required Skills and Qualifications Core Technical Skills Skill Area Requirements Programming Strong proficiency in Python for data manipulation and scripting. Familiarity with standard Python data libraries (e.g., Pandas, NumPy ). Database Expert-level proficiency in SQL (Structured Query Language). Experience writing complex joins, stored procedures, and performing performance tuning. Big Data Concepts Foundational understanding of Big Data More ❯

and pipelines. Required Skills and Qualifications Core Technical Skills Skill Area Requirements Programming Strong proficiency in Python for data manipulation and scripting. Familiarity with standard Python data libraries (e.g., Pandas, NumPy ). Database Expert-level proficiency in SQL (Structured Query Language). Experience writing complex joins, stored procedures, and performing performance tuning. Big Data Concepts Foundational understanding of Big Data More ❯

in Python), Databricks, dbt, Terraform. Advanced knowledge of PostgreSQL, Docker, and CI/CD pipelines. A practical understanding of data modelling, metadata management, and pipeline orchestration. Strong Python skills (Pandas, PySpark, or SQLAlchemy a plus) and SQL. Curiosity about how ML models and BI tools connect back to real-world decisions. Bonus Points Experience building and automating ML deployment pipelines More ❯

of RESTful APIs as well as experience working with both synchronous and asynchronous endpoints Experience with Snowflake or Redshift with a strong understanding of SQL. Proficient in Python and Pandas Experience working with JSON and XML Strong understanding of cloud computing concepts and services (AWS preferably) Experience with Git or equivalent version control systems and CI/CD pipelines. Familiarity More ❯

of RESTful APIs as well as experience working with both synchronous and asynchronous endpoints Experience with Snowflake or Redshift with a strong understanding of SQL. Proficient in Python and Pandas Experience working with JSON and XML Strong understanding of cloud computing concepts and services (AWS preferably) Experience with Git or equivalent version control systems and CI/CD pipelines. Familiarity More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

learning models at scale. Deep familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from More ❯

such as Airflow, Prefect, or Temporal, or by building bespoke pipeline systems for multi-step autonomous processes. You bridge science and engineering — comfortable with scientific computing libraries (NumPy, SciPy, pandas) and familiar with scientific databases and literature formats. What Sets You Apart: You have a research background — perhaps as a former academic researcher or research software engineer in ML/ More ❯

such as Airflow, Prefect, or Temporal, or by building bespoke pipeline systems for multi-step autonomous processes. You bridge science and engineering — comfortable with scientific computing libraries (NumPy, SciPy, pandas) and familiar with scientific databases and literature formats. What Sets You Apart: You have a research background — perhaps as a former academic researcher or research software engineer in ML/ More ❯

applying machine learning or AI techniques Strong programming skills in Python and TypeScript (this is essential) Experience with common Python data/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience building or contributing to TypeScript codebases (e.g. Node.js backends, React frontends, or internal tools) Hands-on exposure to AWS (e.g. EC2, S3, IAM; bonus points for Lambda, ECS More ❯

applying machine learning or AI techniques Strong programming skills in Python and TypeScript (this is essential) Experience with common Python data/ML libraries (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Experience building or contributing to TypeScript codebases (e.g. Node.js backends, React frontends, or internal tools) Hands-on exposure to AWS (e.g. EC2, S3, IAM; bonus points for Lambda, ECS More ❯

quantification, model evaluation, and statistical inference is highly valued. Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data More ❯

quantification, model evaluation, and statistical inference is highly valued. Python expertise: Skilled in building data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data More ❯

as a software engineer or a data engineer and a strong passion to learn. BS/MS in Computer Science or equivalent experience in related fields. Experience in Python, Pandas, PySpark, and Notebooks. SQL knowledge and experience working with relational databases including schema design, access patterns, query performance optimization, etc. Experience with data pipeline technologies like AWS Glue, Airflow, Kafka More ❯

scale up? Having added nearly 100 people to the business this year, they're looking for Quantitative Developers with proficiency in Python, and experience with the Python data libraries (Pandas, NumPy) (preferably) from the Trading world. They also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine More ❯

scale up Having added nearly 100 people to the business this year, they're looking for Quantitative Developers with proficiency in Python, and experience with the Python data libraries (Pandas, NumPy) (preferably) from the Trading world. They also are on the look out for candidates who: Have deep familiarity with Python data ecosystem Understanding of Jupyter notebooks Exposure to machine More ❯

strategies Provide data-driven recommendations to improve engagement metrics Requirements Experience in Customer Marketing Data Science, including applied statistics and machine learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks Experience with ML Ops, including deployment and monitoring Ability to work cross-functionally More ❯

strategies Provide data-driven recommendations to improve engagement metrics Requirements Experience in Customer Marketing Data Science, including applied statistics and machine learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks Experience with ML Ops, including deployment and monitoring Ability to work cross-functionally More ❯

Analytical mindset with interest in systematic trading and quantitative research Nice to Have Exposure to trading systems, market data, or algo/bot development Familiarity with numerical libraries (NumPy, Pandas, Numba, etc.) Understanding of version control, CI/CD, or distributed computing More ❯

Analytical mindset with interest in systematic trading and quantitative research Nice to Have Exposure to trading systems, market data, or algo/bot development Familiarity with numerical libraries (NumPy, Pandas, Numba, etc.) Understanding of version control, CI/CD, or distributed computing More ❯

Stakeholder Communication: Present insights to data labeling experts and technical teams Required Qualifications Statistical Expertise: Strong foundation in statistical analysis, hypothesis testing, and pattern recognition Programming: Proficiency in Python (pandas, scipy, matplotlib/seaborn) or R for data analysis Data Analysis: Experience with exploratory data analysis and creating actionable insights from complex datasets AI/ML Familiarity: Understanding of LLM More ❯

engineering experience, ideally in Treasury or from a hedge fund/buy-side firm Expertise in Python for designing and optimising complex applications Strong proficiency in data tools like Pandas, NumPy, SQL, and real-time data processing Familiarity with DevOps practices, including Linux, cloud platforms, and CI/CD (Docker/Kubernetes is desirable but not essential). Strong communication More ❯

engineering experience, ideally in Treasury or from a hedge fund/buy-side firm Expertise in Python for designing and optimising complex applications Strong proficiency in data tools like Pandas, NumPy, SQL, and real-time data processing Familiarity with DevOps practices, including Linux, cloud platforms, and CI/CD (Docker/Kubernetes is desirable but not essential). Strong communication More ❯

Looking For: Essential: Experience with LLMs (GPT, BERT) and NLP tasks. Fine-tuning pre-trained models for domain-specific applications. Strong Python skills (OOP, PyTorch, Hugging Face, scikit-learn, Pandas, NumPy). Deploying models with Docker, Kubernetes, or serverless platforms. Familiarity with CI/CD, MLOps, and cloud platforms (AWS preferred). Desirable: Named entity recognition, recommendation systems, or image More ❯