1 to 25 of 30 Pandas Jobs in the South East

cloud services like Google Cloud and AWS. Bonus points Startup experience Experience with Python web services (e.g. FastAPI, Django). Data engineering experience using PyData stack technologies (e.g. NumPy, Pandas, etc.) Experience building machine learning systems with LLMs, RAGs utilising embeddings. Technology Frontend: Typescript, , Vercel Backend: Go, Postgres, , Google Cloud Services: GitHub, Sentry, Stytch, OpenAI Perks & Benefits (for UK-based More ❯

Tools for scalable data processing: Kubernetes, Spark â Experience with Java 2D graphics and 3D OpenGL programming. â Experience with scientific computing libraries and frameworks: o Python: NumPy, SciPy, Pandas, TensorFlow (for ML/AI) o C Java: CUDA (for GPU acceleration) o Angular or React o Microservice: Quarkus, Spring Boot, AWS API Gateway o Docker, Kubernetes With over More ❯

and more on reliability and fixes. Key Skills: Investigating and debugging complex data flow and Machine Learning issues within a live, high impact production environment. Extensive Python, NumPy and Pandas is required for this role. You must demonstrate a deep commercial background in the following areas: Extensive Python: Very strong, production-level Python coding and debugging skills. Production Environment: Proven More ❯

continuous improvement initiatives Essential Skills for the AWS Data Engineer: Extensive hands-on experience with AWS data services Strong programming skills in Python (including libraries such as PySpark or Pandas) Solid understanding of data modelling, warehousing and architecture design within cloud environments Experience building and managing ETL/ELT workflows and data pipelines at scale Proficiency with SQL and working More ❯

learning fundamentals, and experimental design. Experience with predictive modeling techniques such as regression, classification, clustering, or time-series forecasting. Proficiency in Python and experience with data science libraries (e.g., Pandas, NumPy, scikit-learn, XGBoost, PyTorch, TensorFlow). Strong experience with SQL and data manipulation across large datasets. Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Plotly, Tableau, or Power BI 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 ❯

Interest in ML application for robotics 7+ years experience as a Senior Software Engineer or ML engineer Demonstrated proficiency in Python, Julia, or R, and related frameworks (PyTorch, Tensorflow, Pandas, Numpy) Knowledge of distributed computing & big data technologies for large datasets (e.g., Spark) and building data pipelines Knowledge of Deep Learning methodologies specific to Computer Vision like YOLO Experience with 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 ❯

Must Have 5+ years professional Python development experience. Extremely effective in writing clean, modern Python code. Experience building and documenting high-quality APIs for developers. Deep Python ecosystem expertise: Pandas, Numpy, Bokeh, PyArrow, matplotlib, IPyWidgets, Jupyter, uv, etc. Proven experience building large data pipelines/ETL workflows. Comfortable working in Jupyter notebooks. An understanding of crypto or TradFi markets and More ❯

master’s degree in a STEM subject (Mathematics, Computer Science or Engineering) Experience working in a data science or consulting role In-depth experience of working with Python and Pandas An entrepreneurial spirit and drive to work in an early stage start-up A curious mindset to understand how we can improve things and better help our clients address commercial More ❯

time series forecasting, reinforcement learning, optimization, or conversational AI. Familiarity with Python or similar programming languages and common toolkits and AI/ML frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Pandas, NumPy). Strong analytical and problem-solving skills. Ability to design machine learning experiments and define model performance metrics that ensure AI outputs are aligned with business goals. Ability to More ❯

always work with our data, so you will need to understand how to develop your own models Strong programming skills and experience working with Python, scikit-learn, SciPy, NumPy, Pandas and Jupyter Previous experience in finance is not required, although an interest in finance and the motivation to rapidly learn more is a prerequisite for working here. Why should you More ❯

to leverage AI tooling to get bootstrapped quickly is a must. Core AI & Machine Learning Python Vertex AI/Hugging Face LangChain/BAML — LLM frameworks Langfuse, LangSmith — Observability Pandas, NumPy, scikit-learn, PyTorch — Data & ML stack Data & Infrastructure BigQuery — Cloud data warehouse PostgreSQL — Application data Pulumi — Infrastructure as Code (TypeScript) Google Cloud Platform (GCP) — Cloud provider GitHub Actions — CI More ❯

proofs-of-concept , model monitoring , and adoption of emerging AI tech. What We’re Looking For 5+ years in data engineering, with team or project leadership experience. Advanced Python (Pandas, PyTorch, TensorFlow, Scikit-learn). Strong AWS/GCP , MySQL , and CI/CD experience; Docker/Kubernetes a plus. Excellent communication, organisation, and problem-solving skills. Passion for innovation More ❯

or similar role focused on Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some exposure to web scraping tools More ❯

or similar role focused on Python coding. It is essential to have good knowledge of Python built in data types/functionality as well as associated tools such as Pandas/Polars, and web frameworks. The ideal candidate will be passionate about the latest AI/Machine Learning/Automation techniques and tools, with some exposure to web scraping tools More ❯

users Present findings and recommendations to non-technical stakeholders 3. Ideal Qualifications 5+ years of applied data science or analytics experience in business settings Proficiency in Python or R (pandas, NumPy, Jupyter) and strong SQL skills Experience with data visualization tools (e.g., Tableau, Power BI) Solid understanding of statistical modeling, experimentation, and A/B testing Strong communication skills for More ❯

key strategic initiatives, including price, volume, and mix analysis and margin optimisation . Tech Environment Core Skills: SQL (essential), Power BI (advantageous) Platform: Microsoft Fabric (mid-implementation) Languages: Python (pandas/numpy - desirable, not essential) Other: Salesforce & Google Analytics exposure beneficial About You Proven experience as an Insight Analyst , ideally in wholesale, distribution, or another product-heavy industry. Strong knowledge More ❯

kinetics. Interest in simulation, modeling workflows, and their application in real-world pharma/biotech contexts. Basic to intermediate Python programming skills, especially with scientific libraries (e.g., NumPy, SciPy, pandas). Nice to Have Experience with Pyomo or CasADi. Familiarity with bioprocesses or pharma case studies. Curiosity about AI, workflow automation, or cloud-based platforms. Soft Skills Proactive, reliable, and More ❯

if you: Have over 3+ years of professional experience in data science or applied analytics. Are highly skilled in Python and Jupyter notebooks. Have experience using libraries including numpy, pandas, scipy, sympy, scikit-learn, torch, tensorflow. Have a bachelor's degree in data science, statistics, computer science, or related field in the U.S., Canada, New Zealand, UK or Australia. Have More ❯

recommendation. Familiarity with state-of-the-art practice in these domains Proficient in Python, and experience with machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Scientific thinking, ability to design experiments and training frameworks, and to outline and evaluate intrinsic and extrinsic metrics for model performance aligned with business goals Solid written and spoken communication More ❯

to full time after the internship. Have experience programming in Python, C/C++, Java and/or experience with statistical analysis, numerical programming, or machine learning in Python, Pandas, R. Are an ambitious entrepreneur with a track record of exceptional intellectual achievement. Are a self starter, comfortable taking initiative and working independently in a past faced and dynamic environment. More ❯

practical application (e.g., regression, classification, clustering, time-series forecasting, survival analysis). Solid object-oriented programming skills in Python and hands-on expertise with the core data science stack (Pandas, Numpy, Scikit-learn, XGBoost/LightGBM). A proven ability to break down vague, complex problems into concrete, solvable steps. Excellent communication and data storytelling skills. You can build strong More ❯

of-concepts and assist the business with evaluations to measure success and estimate value proposition. Essential Criteria: * Extensive experience with Python and data science Python packages (e.g. scikit-learn, pandas, numpy, etc) * Understanding of data science concepts, AI/ML models, evaluation approaches, and data science applications to enhance business processes * Proven hands-on experience in Microsoft Azure ML Studio More ❯

experience as a Data Scientist , ideally in a government or large-scale enterprise environment. Strong Python programming skills, including experience with data science and AI/ML frameworks (e.g., Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow). Experience developing and fine-tuning LLMs and working with generative AI tools. Hands-on experience with Microsoft Azure (Azure ML, Databricks, or other AI More ❯