1 to 25 of 264 Pandas Jobs in the South East

depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time More ❯

depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time More ❯

depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time More ❯

Desired Skills and Experience: Kafka and message bus/queue expertise 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: Collaborate with More ❯

experience. You’ll help streamline client onboarding, build robust integrations, and play a key role in evolving the platform. 🛠 Tech Stack & Methodology Python (Dataclasses, Pandas, Asyncio) PostgreSQL , AWS (ECS, Lambda, SQS) Agile (XP), TDD, CI/CD, and strong automation culture If you're familiar with these tools—or eager More ❯

experience. You’ll help streamline client onboarding, build robust integrations, and play a key role in evolving the platform. 🛠 Tech Stack & Methodology Python (Dataclasses, Pandas, Asyncio) PostgreSQL , AWS (ECS, Lambda, SQS) Agile (XP), TDD, CI/CD, and strong automation culture If you're familiar with these tools—or eager More ❯

or senior role. Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure More ❯

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 improve all our colleagues More ❯

ability to collaborate with both technical and non-technical teams This role is 70% hands on, 30% management Technical Expertise Required - Python - proficiency with Pandas, Numpy, SQLAlchemy, FastAPI, and Pydantic MySQL, PostgreSQL, and Redis Hands-on experience with Google Cloud Platform (GCP) services like Pub/Sub, Cloud Run, VMs More ❯

ability to collaborate with both technical and non-technical teams This role is 70% hands on, 30% management Technical Expertise Required - Python - proficiency with Pandas, Numpy, SQLAlchemy, FastAPI, and Pydantic MySQL, PostgreSQL, and Redis Hands-on experience with Google Cloud Platform (GCP) services like Pub/Sub, Cloud Run, VMs More ❯

ability to collaborate with both technical and non-technical teams This role is 70% hands on, 30% management Technical Expertise Required - Python - proficiency with Pandas, Numpy, SQLAlchemy, FastAPI, and Pydantic MySQL, PostgreSQL, and Redis Hands-on experience with Google Cloud Platform (GCP) services like Pub/Sub, Cloud Run, VMs More ❯

and business intelligence A good understanding of Python, including fundamental knowledge and a willingness to learn, along with familiarity with packages such as NumPy, pandas, and scikit-learn. Proficiency in SQL is required, along with experience in Unix and familiarity with scheduling tools like Tidal and Airflow. Good understanding of More ❯

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 record More ❯

with retrieval-augmented generation (RAG) systems Knowledge of optimization techniques for reducing LLM latency and computational costs Software Engineering & Architecture Strong Python development skills (pandas, numpy, scikit-learn, PyTorch/TensorFlow) Experience with web frameworks (Streamlit, FastAPI, or Flask) and frontend technologies Database design and optimization (PostgreSQL preferred) for large More ❯

optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing More ❯

optimization. Experience with distributed systems, parallel computing, and high-performance processing of large datasets. Strong experience in data pipelines, working with tools such as Pandas, NumPy, and SQL/NoSQL databases. Proven experience working in fast-paced environments, ideally within trading, financial services, or high-frequency environments. Proficiency in developing More ❯

with experience in backend frameworks like Flask , FastAPI , or Django . Ability to write efficient, reusable, and scalable code. Experience with libraries like NumPy , Pandas , SciPy , or any others commonly used in data processing or modelling. Strong understanding of data structures , algorithms , and complexity analysis . Mathematical or Computational Modelling More ❯

Frameworks : PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data More ❯

Frameworks : PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data More ❯

Frameworks : PyCaret, Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data More ❯

including 3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow More ❯

including 3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow More ❯

including 3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow More ❯

including 3+ years of Python in production (e.g., Flask, Django, Gunicorn, SQLAlchemy, Psycopg2). Strong background in working with large datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow More ❯

a revelant role. This will mean exposure to market data vendors, ability to communicate with traders and mentoring junior engineers. Tech stack: Deep Python, Pandas, AWS, Airflow, Kubernetes, ETL, SQL Please apply if this of interest More ❯