22 of 22 Pandas Jobs in the South East

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 ❯

flows and ML issues in live production environments. We're looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer 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 ❯

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 ❯

and refining them to strong results. Experienced in engaging with non-technical partners to scope, design and build an appropriate ML solution. Proficient with Python data science stack, e.g., pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with More ❯

and a desire to understand complex issues Beneficial experience • Experience in trading or execution roles • Experience with equity/credit markets • Research using large, messy datasets • Familiarity with Linux • Pandas Benefits: Working alongside other extremely talented and driven engineers Extremely lucrative salary, bonus and benefits More ❯

large, complex datasets. Desirable Experience & Skills Practical knowledge of data engineering practices (designing and building robust data pipelines) Knowledge of python and core libraries applicable to data science (e.g., pandas, numpy, statsmodel More ❯

AI models. Collaborate with data scientists, software engineers, and subject-matter experts to deliver innovative solutions. Essential Skills & Experience Advanced Python programming skills with hands-on experience using NumPy, Pandas, Scikit-learn, Langchain, LlamaIndex , and Azure AI Foundry . Proven experience working with Azure cloud services and Generative AI R&D. Strong understanding of machine learning, data modelling , and natural More ❯

predictive model- Clear explainability on what drives user clicks- A functional internal tool for non-technical stakeholders- Documentation and guidance for productionisation Required Skills Must-Have: Expert-level Python (Pandas, modelling libraries such as Scikit-learn) SQL AWS cloud experience Proven end-to-end ownership of data science solutions Model explainability (SHAP, LIME, feature importance) Ability to build simple dashboards More ❯

the latest developments in AI, machine learning, and data science methodologies. Experienced Needed: Masters or PhD in a STEM subject Proficiency in Python, with experience in libraries such as pandas, scikit-learn, TensorFlow, or PyTorch. Solid SQL skills and experience working with relational databases. Exposure to cloud platforms (AWS, GCP, or Azure) would be advantageous. Strong analytical and problem-solving More ❯

with active SC will be prioritised) Within this role, you will be responsible for: * Cleaning and processing tabular data (Excel, CSV, databases) * Building data transformation pipelines using Python and pandas * Writing SQL queries to extract and manipulate relational data * Implementing data validation and quality assurance processes * Working with JSON, XML, and CSV formats * Supporting metadata cataloging and reference data management 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 ❯

Programming: Strong understanding of OOP principles, functions, classes, list comprehensions, generators, and exception handling. Experience managing virtual environments and dependencies using pip or venv. Data Manipulation & Analysis: Proficiency with Pandas , NumPy (and optionally Polars). Strong data cleaning, transformation, grouping, merging, and aggregation skills. Experience with SQL for data querying. Software Engineering Best Practices: Experience with Git for version control. 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 ❯

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 ❯

model performance. What We're Looking For A Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field. Strong experience with Python and data science libraries (Pandas, Scikit-learn, etc.). Solid understanding of machine learning concepts and algorithms . Interest in working with real-world industrial or sensor data . Exposure to Apache Airflow and/ More ❯

moving environments and create clarity where it's needed most. Your Technical Toolkit Strong foundations in causal inference, experimentation, and statistical modelling. Hands-on experience with SQL and Python (Pandas, SciPy, etc.) Deep understanding of product metrics and experience in product-led organisations. Why You'll Love This Role Real Impact: Work at the intersection of robotics, AI, logistics, and More ❯

AI Services). Experience with a major conversational AI platform (Google Dialogflow, Amazon Lex, Rasa, or similar). A solid understanding of core Python ML libraries (Keras, scikit-learn, Pandas) and deep learning frameworks (TensorFlow, PyTorch). Desirable (but not essential) experience: Working with tools/interfaces for AI applications e.g. MCP protocol. Training traditional ML and DL models using More ❯

Machine Learning Engineer Machine Learning Engineer – AI for Advanced Materials – Oxford (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We’re looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that’s reinventing how the … seeking Machine Learning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that’s fusing AI, science, and engineering to More ❯

Machine Learning Engineer Machine Learning Engineer - AI for Advanced Materials - Oxford/Remote (UK) (Tech stack: Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, AWS, Azure, GCP, Pandas, NumPy, SciPy, CI/CD, MLOps, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform) We're looking for a Machine Learning Engineer to join a rapidly scaling deep-tech company that's … seeking Machine Learning Engineers with experience in some or all of the following (full training provided to fill any gaps): Python, PyTorch, TensorFlow, Scikit-learn, MLflow, Airflow, Docker, Kubernetes, Pandas, NumPy, SciPy, CI/CD, Data Visualization, Bayesian Modelling, Probabilistic Programming, Terraform, Azure, AWS, GCP, Git, and Agile methodologies. Join a team that's fusing AI, science, and engineering to More ❯

Data Scientist, Machine Learning Engineer, ML Engineer, Data Science Engineer, High-Performance Engineering, Python, Data, Pandas, numpy, scikit-learn, pytorch - Oxford - up to 55K About the Role: Join an elite engineering organisation's Software Engineering & Data team, where you'll develop cutting-edge machine learning solutions that directly impact performance at the highest level of competition. This is a unique … MSc degree in a relevant field for Data Science 2+ years development experience in Python and machine learning techniques (production or laboratory) Strong knowledge of Python data science packages: Pandas, numpy, scikit-learn, pytorch Experience with Machine Learning techniques: Neural Networks, XGBoost Understanding of pipelines and deployment technologies: Azure DevOps, Docker, GitHub Actions Good understanding of architecture and design patterns More ❯

with: Proficient Python Programming Key skills: Functions, classes, and object-oriented programming, List comprehensions, generators, Error handling, Working with virtual environments and package management (pip, venv) Data Manipulation & Analysis (Pandas & NumPy) Key libraries: pandas, numpy, (optional: polars) Key skills: Data cleaning and preprocessing, Handling missing values, grouping, merging, pivoting, aggregations, and SQL Software Engineering Best Practices Key practices: Version control More ❯