11 of 11 Permanent Pandas Jobs in Oxfordshire

Key Skills & Experience: 5+ years of relevant industry experience, ideally within financial services, capital markets, or asset management sectors. Proficient in Python 3, including pandas, GeoPandas, boto3, Pydantic, and Data Version Control (DVC). Familiar with Django 4 and core API development. Strong hands-on experience with AWS cloud infrastructure More ❯

Science, Engineering, or a related field (or equivalent practical experience). Technical Skills: Deep expertise in Python, including libraries such as Django, Flask, FastAPI, Pandas and NumPy. Strong knowledge of relational and non-relational databases (e.g., PostgreSQL, MongoDB, Redis). Proficiency with cloud platforms (e.g., AWS, Azure, GCP) and containerization More ❯

or CloudFormation) Solid understanding of testing frameworks and version control systems (e.g. Git) Nice to Have: Experience with data engineering tools such as Airflow, Pandas, or Spark Exposure to serverless architectures using AWS Lambda Familiarity with monitoring and logging tools (e.g. CloudWatch, Prometheus) Previous experience working in regulated or high 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 ❯

and the ability to apply this process when handling structured or unstructured data Confident with using common data science tooling such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy API testing and security tools: Postman, Burp Suite, OWASP ZAP, etc. Strong knowledge of database management systems (DBMS) such as MySQL Hands More ❯

and the ability to apply this process when handling structured or unstructured data Confident with using common data science tooling such as Jupyter notebooks, pandas, matplotlib, seaborn, numpy API testing and security tools: Postman, Burp Suite, OWASP ZAP, etc. Strong knowledge of database management systems (DBMS) such as MySQL Hands More ❯

of Python. Strong English proficiency. Desirable Qualifications Knowledge of any machine learning framework (e.g. Torch, huggingface, ...) and/or data analysis platform (e.g. Pandas). Past experience with open source projects. Past experience in community engagement projects. Familiarity with Scrum/Agile software development practices. Our Offer Competitive salary More ❯

reliability and cost, or improving our search service Tech Stack: Platform: AWS, Pulumi, Docker, Prefect, Github actions, Grafana cloud monitoring Data Science: Python, PyTorch, Pandas, Spacy, Huggingface, Numpy, Streamlit, Argilla, Weights and Biases Backend: Python, FastAPI, PostgreSQL, Vespa, SQLAlchemy, AWS Batch, Lambda, S3 Frontend: React, Next.js Key skills and experience More ❯

building and implementing forecasting models using modern ML techniques. Deep understanding of time series analysis, statistics, and forecasting methodologies. Production-level Python programming skills (Pandas, Polars, Scikit-learn, NumPy, SciPy). Comfort working in a collaborative, cross-functional environment. Please note, this role cannot offer sponsorship at this stage More ❯

technology on highly visible and large-scale projects. What you’ll bring to the role Strong grounding in ML approaches, techniques and frameworks Python, Pandas, Tensor Flow, Scikit-learn, Numpy, SciPy Experience deploying to the cloud and working with Azure (Azure DevOps, Azure ML, Azure SQL, ADF etc.) Able to More ❯

making. Required Qualifications: Basic knowledge of Python and/or SQL. Interest in data analytics, statistics, or machine learning. Familiarity with tools like Excel, Pandas, Numpy, or visualization libraries. Strong communication and time management skills. Preferred (Not Mandatory): Previous coursework, projects, or online certifications in data science. Understanding of data More ❯